Overview

Dataset statistics

Number of variables158
Number of observations73658
Missing cells406206
Missing cells (%)3.5%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory91.4 MiB
Average record size in memory1.3 KiB

Variable types

Categorical152
Numeric5
Boolean1

Alerts

UniqueID has a high cardinality: 73658 distinct valuesHigh cardinality
Incident Number has a high cardinality: 64258 distinct valuesHigh cardinality
Incident Date has a high cardinality: 4299 distinct valuesHigh cardinality
Species Common Name has a high cardinality: 321 distinct valuesHigh cardinality
Latitude Public is highly overall correlated with Field Unit and 1 other fieldsHigh correlation
Longitude Public is highly overall correlated with Field Unit and 1 other fieldsHigh correlation
Total Staff Involved is highly overall correlated with Total Staff HoursHigh correlation
Total Staff Hours is highly overall correlated with Total Staff InvolvedHigh correlation
Sum of Number of Animals is highly overall correlated with Animal Response to DeterrentsHigh correlation
Field Unit is highly overall correlated with Latitude Public and 6 other fieldsHigh correlation
Protected Heritage Area is highly overall correlated with Latitude Public and 6 other fieldsHigh correlation
Animal Health Status is highly overall correlated with Activity Type_Canyoneering and 4 other fieldsHigh correlation
Cause of Animal Health Status is highly overall correlated with Activity Type_Canyoneering and 17 other fieldsHigh correlation
Animal Behaviour is highly overall correlated with Activity Type_Bush Party and 4 other fieldsHigh correlation
Reason for Animal Behaviour is highly overall correlated with Activity Type_Bush Party and 7 other fieldsHigh correlation
Animal Attractant is highly overall correlated with Activity Type_Canyoneering and 13 other fieldsHigh correlation
Deterrents Used is highly overall correlated with Activity Type_Bush Party and 20 other fieldsHigh correlation
Animal Response to Deterrents is highly overall correlated with Sum of Number of Animals and 31 other fieldsHigh correlation
Activity Type_Boating - Commercial is highly overall correlated with Animal Response to DeterrentsHigh correlation
Activity Type_Boating - Motorized Pleasure Craft is highly overall correlated with Animal Response to DeterrentsHigh correlation
Activity Type_Bush Party is highly overall correlated with Animal Behaviour and 3 other fieldsHigh correlation
Activity Type_Canyoneering is highly overall correlated with Animal Health Status and 4 other fieldsHigh correlation
Activity Type_Climbing - Mountaineering is highly overall correlated with Animal Response to DeterrentsHigh correlation
Activity Type_Climbing - Technical Rock is highly overall correlated with Cause of Animal Health StatusHigh correlation
Activity Type_Climbing - Waterfall Ice is highly overall correlated with Cause of Animal Health Status and 3 other fieldsHigh correlation
Activity Type_Cycling - Winter is highly overall correlated with Cause of Animal Health Status and 2 other fieldsHigh correlation
Activity Type_Dog Walking is highly overall correlated with Animal AttractantHigh correlation
Activity Type_Dogsledding is highly overall correlated with Cause of Animal Health StatusHigh correlation
Activity Type_Driving is highly overall correlated with Cause of Animal Health StatusHigh correlation
Activity Type_Flight - HETS is highly overall correlated with Cause of Animal Health Status and 3 other fieldsHigh correlation
Activity Type_Flight - Hang-gliding/Parapenting is highly overall correlated with Cause of Animal Health Status and 2 other fieldsHigh correlation
Activity Type_Kayaking - Swiftwater is highly overall correlated with Deterrents Used and 1 other fieldsHigh correlation
Activity Type_Not Applicable is highly overall correlated with Animal Response to DeterrentsHigh correlation
Activity Type_Orienteering / Geocaching is highly overall correlated with Cause of Animal Health Status and 3 other fieldsHigh correlation
Activity Type_Paddleboarding - Coastal is highly overall correlated with Animal Health Status and 6 other fieldsHigh correlation
Activity Type_Park Ops - Avalanche Forecasting is highly overall correlated with Animal Behaviour and 1 other fieldsHigh correlation
Activity Type_Rafting - Flatwater is highly overall correlated with Reason for Animal Behaviour and 1 other fieldsHigh correlation
Activity Type_Railway is highly overall correlated with Animal AttractantHigh correlation
Activity Type_Roller Sports is highly overall correlated with Cause of Animal Health StatusHigh correlation
Activity Type_Sail Sports - Wind / Kite Surfing is highly overall correlated with Animal Behaviour and 4 other fieldsHigh correlation
Activity Type_Scrambling is highly overall correlated with Cause of Animal Health Status and 5 other fieldsHigh correlation
Activity Type_Skiing/Boarding - Ski Resort Out of Bounds is highly overall correlated with Deterrents Used and 1 other fieldsHigh correlation
Activity Type_Snowmobiling is highly overall correlated with Animal Attractant and 2 other fieldsHigh correlation
Activity Type_Snowshoeing is highly overall correlated with Animal Response to DeterrentsHigh correlation
Activity Type_Surfing is highly overall correlated with Animal Response to DeterrentsHigh correlation
Activity Type_Swimming - Cliff Jumping is highly overall correlated with Animal Health Status and 2 other fieldsHigh correlation
Activity Type_Swimming - Coastal is highly overall correlated with Animal Attractant and 2 other fieldsHigh correlation
Activity Type_Swimming - Swiftwater is highly overall correlated with Animal Response to DeterrentsHigh correlation
Activity Type_Tubing / River Drifting is highly overall correlated with Animal Attractant and 2 other fieldsHigh correlation
Activity Type_Via-Ferrata is highly overall correlated with Animal Attractant and 2 other fieldsHigh correlation
Activity Type_nan is highly overall correlated with Animal Response to DeterrentsHigh correlation
Response Type_ is highly overall correlated with Cause of Animal Health Status and 2 other fieldsHigh correlation
Response Type_Close Road is highly overall correlated with Field Unit and 6 other fieldsHigh correlation
Response Type_Collect Sample is highly overall correlated with Response Type_Close Road and 1 other fieldsHigh correlation
Response Type_Cull is highly overall correlated with Field Unit and 7 other fieldsHigh correlation
Response Type_Destroy Animal is highly overall correlated with Deterrents UsedHigh correlation
Response Type_Dispose Carcass is highly overall correlated with Animal Health StatusHigh correlation
Response Type_Haze - Hard is highly overall correlated with Deterrents UsedHigh correlation
Response Type_Haze - Soft is highly overall correlated with Deterrents Used and 1 other fieldsHigh correlation
Response Type_Infrastructure modification is highly overall correlated with Animal Response to DeterrentsHigh correlation
Response Type_Issue Prohibited Activity Order is highly overall correlated with Animal Response to DeterrentsHigh correlation
Response Type_Issue Stop Work Order is highly overall correlated with Animal Health Status and 4 other fieldsHigh correlation
Response Type_Monitor - Camera is highly overall correlated with Field Unit and 4 other fieldsHigh correlation
Response Type_Necropsy is highly overall correlated with Field Unit and 3 other fieldsHigh correlation
Response Type_nan is highly overall correlated with Animal Response to DeterrentsHigh correlation
Within Park is highly imbalanced (90.8%)Imbalance
Species Common Name is highly imbalanced (56.3%)Imbalance
Activity Type_Backpacking – Multiday Trips is highly imbalanced (93.9%)Imbalance
Activity Type_Beach Recreation is highly imbalanced (93.0%)Imbalance
Activity Type_Boating - Coastal/Marine is highly imbalanced (99.4%)Imbalance
Activity Type_Boating - Commercial is highly imbalanced (99.8%)Imbalance
Activity Type_Boating - Motorized Pleasure Craft is highly imbalanced (99.1%)Imbalance
Activity Type_Bush Party is highly imbalanced (> 99.9%)Imbalance
Activity Type_Camping - Backcountry is highly imbalanced (91.7%)Imbalance
Activity Type_Camping - Frontcountry is highly imbalanced (61.1%)Imbalance
Activity Type_Camping - Huts and Lodges is highly imbalanced (96.0%)Imbalance
Activity Type_Camping - Winter Frontcountry is highly imbalanced (99.7%)Imbalance
Activity Type_Canoeing - Flatwater is highly imbalanced (99.3%)Imbalance
Activity Type_Canoeing - Swiftwater is highly imbalanced (99.7%)Imbalance
Activity Type_Canyoneering is highly imbalanced (> 99.9%)Imbalance
Activity Type_Climbing - Mountaineering is highly imbalanced (99.9%)Imbalance
Activity Type_Climbing - Technical Rock is highly imbalanced (99.9%)Imbalance
Activity Type_Climbing - Waterfall Ice is highly imbalanced (99.9%)Imbalance
Activity Type_Commercial Transportation Operation is highly imbalanced (98.0%)Imbalance
Activity Type_Cycling is highly imbalanced (98.3%)Imbalance
Activity Type_Cycling - Mountain Biking is highly imbalanced (97.3%)Imbalance
Activity Type_Cycling - Road/Shared Path is highly imbalanced (95.8%)Imbalance
Activity Type_Cycling - Winter is highly imbalanced (99.9%)Imbalance
Activity Type_Dog Walking is highly imbalanced (93.2%)Imbalance
Activity Type_Dogsledding is highly imbalanced (> 99.9%)Imbalance
Activity Type_Domestic Residence Activity is highly imbalanced (94.2%)Imbalance
Activity Type_Field Sports is highly imbalanced (98.4%)Imbalance
Activity Type_Fishing is highly imbalanced (99.2%)Imbalance
Activity Type_Flight - HETS is highly imbalanced (> 99.9%)Imbalance
Activity Type_Flight - Hang-gliding/Parapenting is highly imbalanced (99.9%)Imbalance
Activity Type_Flight - Helicopter is highly imbalanced (99.9%)Imbalance
Activity Type_Flight - Sightseeing/Site Access is highly imbalanced (99.9%)Imbalance
Activity Type_Golfing is highly imbalanced (84.9%)Imbalance
Activity Type_Heritage Activity - Bird Watching is highly imbalanced (99.5%)Imbalance
Activity Type_Heritage Activity - History Activities is highly imbalanced (98.7%)Imbalance
Activity Type_Heritage Activity - Photography and Art is highly imbalanced (97.7%)Imbalance
Activity Type_Heritage Activity - Sightseeing is highly imbalanced (95.0%)Imbalance
Activity Type_Heritage Activity - Wildlife Observation is highly imbalanced (92.0%)Imbalance
Activity Type_Hiking / Walking is highly imbalanced (60.8%)Imbalance
Activity Type_Horse Riding - Day Trip is highly imbalanced (98.0%)Imbalance
Activity Type_Horse Riding - Multiday is highly imbalanced (99.7%)Imbalance
Activity Type_Ice Skating is highly imbalanced (99.9%)Imbalance
Activity Type_Kayaking - Coastal is highly imbalanced (99.8%)Imbalance
Activity Type_Kayaking - Flatwater is highly imbalanced (99.7%)Imbalance
Activity Type_Kayaking - Swiftwater is highly imbalanced (> 99.9%)Imbalance
Activity Type_Mooring is highly imbalanced (> 99.9%)Imbalance
Activity Type_Not Applicable is highly imbalanced (99.9%)Imbalance
Activity Type_Orienteering / Geocaching is highly imbalanced (> 99.9%)Imbalance
Activity Type_Other is highly imbalanced (94.9%)Imbalance
Activity Type_Paddleboarding - Coastal is highly imbalanced (> 99.9%)Imbalance
Activity Type_Paddleboarding - Flatwater is highly imbalanced (99.8%)Imbalance
Activity Type_Park Operations is highly imbalanced (68.5%)Imbalance
Activity Type_Park Ops - Avalanche Forecasting is highly imbalanced (99.9%)Imbalance
Activity Type_Park Ops - Avalanche Control is highly imbalanced (99.9%)Imbalance
Activity Type_Park Ops - Search and Rescue is highly imbalanced (> 99.9%)Imbalance
Activity Type_Park Ops - Training is highly imbalanced (99.9%)Imbalance
Activity Type_Picnicking / BBQ is highly imbalanced (93.4%)Imbalance
Activity Type_Playground Activities is highly imbalanced (99.5%)Imbalance
Activity Type_Rafting - Flatwater is highly imbalanced (99.9%)Imbalance
Activity Type_Rafting - Swiftwater is highly imbalanced (99.9%)Imbalance
Activity Type_Railway is highly imbalanced (74.1%)Imbalance
Activity Type_Research - Scientific/Social is highly imbalanced (98.9%)Imbalance
Activity Type_Resource Harvesting - Hunting/Fishing/Gathering/Trapping is highly imbalanced (99.3%)Imbalance
Activity Type_Roller Sports is highly imbalanced (99.9%)Imbalance
Activity Type_Running - Road is highly imbalanced (99.3%)Imbalance
Activity Type_Running - Trail is highly imbalanced (98.8%)Imbalance
Activity Type_Sail Sports - Wind / Kite Surfing is highly imbalanced (> 99.9%)Imbalance
Activity Type_Scrambling is highly imbalanced (99.9%)Imbalance
Activity Type_Skiing - Crosscountry is highly imbalanced (99.0%)Imbalance
Activity Type_Skiing/Boarding - Backcountry is highly imbalanced (99.3%)Imbalance
Activity Type_Skiing/Boarding - Ski Resort In Bounds is highly imbalanced (99.2%)Imbalance
Activity Type_Skiing/Boarding - Ski Resort Out of Bounds is highly imbalanced (99.9%)Imbalance
Activity Type_Sledding/Tobogganning is highly imbalanced (99.9%)Imbalance
Activity Type_Snowmobiling is highly imbalanced (> 99.9%)Imbalance
Activity Type_Snowshoeing is highly imbalanced (99.8%)Imbalance
Activity Type_Special Event - Participative Audience is highly imbalanced (99.7%)Imbalance
Activity Type_Special Events - Passive Audience is highly imbalanced (99.8%)Imbalance
Activity Type_Stakeholder Operations is highly imbalanced (74.1%)Imbalance
Activity Type_Surfing is highly imbalanced (99.9%)Imbalance
Activity Type_Swimming - Cliff Jumping is highly imbalanced (> 99.9%)Imbalance
Activity Type_Swimming - Coastal is highly imbalanced (> 99.9%)Imbalance
Activity Type_Swimming - Facilities is highly imbalanced (99.8%)Imbalance
Activity Type_Swimming - Flat Water is highly imbalanced (99.6%)Imbalance
Activity Type_Swimming - Swiftwater is highly imbalanced (99.8%)Imbalance
Activity Type_Tram/Ski Lift/Gondola is highly imbalanced (99.4%)Imbalance
Activity Type_Tubing / River Drifting is highly imbalanced (> 99.9%)Imbalance
Activity Type_Unknown is highly imbalanced (97.7%)Imbalance
Activity Type_Via-Ferrata is highly imbalanced (> 99.9%)Imbalance
Activity Type_nan is highly imbalanced (57.9%)Imbalance
Response Type_ is highly imbalanced (99.9%)Imbalance
Response Type_Assist Visitor is highly imbalanced (96.6%)Imbalance
Response Type_Assist other Agency is highly imbalanced (96.0%)Imbalance
Response Type_Assist other Field Unit is highly imbalanced (99.8%)Imbalance
Response Type_Attractant Management is highly imbalanced (94.9%)Imbalance
Response Type_Aversive Conditioning is highly imbalanced (97.9%)Imbalance
Response Type_Capture and transport to captivity is highly imbalanced (98.9%)Imbalance
Response Type_Clean Up is highly imbalanced (88.9%)Imbalance
Response Type_Close Area is highly imbalanced (89.2%)Imbalance
Response Type_Close Road is highly imbalanced (97.3%)Imbalance
Response Type_Collar is highly imbalanced (99.4%)Imbalance
Response Type_Collect Sample is highly imbalanced (93.1%)Imbalance
Response Type_Cull is highly imbalanced (97.5%)Imbalance
Response Type_Destroy Animal is highly imbalanced (91.2%)Imbalance
Response Type_Disentangle is highly imbalanced (98.1%)Imbalance
Response Type_Dispatch other Agency is highly imbalanced (97.9%)Imbalance
Response Type_Disperse Wildlife Jam is highly imbalanced (73.7%)Imbalance
Response Type_Dispose Carcass is highly imbalanced (64.0%)Imbalance
Response Type_Ear Tag is highly imbalanced (97.8%)Imbalance
Response Type_Euthanize is highly imbalanced (95.7%)Imbalance
Response Type_Evacuate Visitor is highly imbalanced (98.2%)Imbalance
Response Type_Haze - Hard is highly imbalanced (76.6%)Imbalance
Response Type_Immobilize Animal is highly imbalanced (98.3%)Imbalance
Response Type_Inform Visitor is highly imbalanced (74.7%)Imbalance
Response Type_Infrastructure modification is highly imbalanced (96.4%)Imbalance
Response Type_Issue Prohibited Activity Order is highly imbalanced (99.4%)Imbalance
Response Type_Issue Restricted Activity Order is highly imbalanced (98.7%)Imbalance
Response Type_Issue Stop Work Order is highly imbalanced (99.9%)Imbalance
Response Type_Leave on Landscape is highly imbalanced (89.5%)Imbalance
Response Type_Mark - paint is highly imbalanced (98.7%)Imbalance
Response Type_Monitor - Camera is highly imbalanced (95.5%)Imbalance
Response Type_Monitor - visitor and staff sighting is highly imbalanced (70.6%)Imbalance
Response Type_Necropsy is highly imbalanced (94.9%)Imbalance
Response Type_No response required is highly imbalanced (96.2%)Imbalance
Response Type_Not Applicable is highly imbalanced (95.7%)Imbalance
Response Type_Refer incident to other agency is highly imbalanced (93.1%)Imbalance
Response Type_Rehabilitate area is highly imbalanced (99.5%)Imbalance
Response Type_Relocate animal (s) is highly imbalanced (78.6%)Imbalance
Response Type_Request assistance - other Agency is highly imbalanced (96.4%)Imbalance
Response Type_Request assistance - police is highly imbalanced (97.1%)Imbalance
Response Type_Traffic control is highly imbalanced (80.5%)Imbalance
Response Type_Translocate is highly imbalanced (99.4%)Imbalance
Response Type_Trap or snare is highly imbalanced (85.1%)Imbalance
Response Type_Unable to respond is highly imbalanced (93.6%)Imbalance
Response Type_Warning signs is highly imbalanced (85.6%)Imbalance
Response Type_nan is highly imbalanced (78.5%)Imbalance
Animal Health Status has 32173 (43.7%) missing valuesMissing
Cause of Animal Health Status has 60461 (82.1%) missing valuesMissing
Animal Behaviour has 27983 (38.0%) missing valuesMissing
Reason for Animal Behaviour has 47521 (64.5%) missing valuesMissing
Animal Attractant has 48864 (66.3%) missing valuesMissing
Deterrents Used has 54118 (73.5%) missing valuesMissing
Animal Response to Deterrents has 63156 (85.7%) missing valuesMissing
Response Type_ has 1462 (2.0%) missing valuesMissing
Response Type_Assist Visitor has 1462 (2.0%) missing valuesMissing
Response Type_Assist other Agency has 1462 (2.0%) missing valuesMissing
Response Type_Assist other Field Unit has 1462 (2.0%) missing valuesMissing
Response Type_Attractant Management has 1462 (2.0%) missing valuesMissing
Response Type_Aversive Conditioning has 1462 (2.0%) missing valuesMissing
Response Type_Capture and transport to captivity has 1462 (2.0%) missing valuesMissing
Response Type_Clean Up has 1462 (2.0%) missing valuesMissing
Response Type_Close Area has 1462 (2.0%) missing valuesMissing
Response Type_Close Road has 1462 (2.0%) missing valuesMissing
Response Type_Collar has 1462 (2.0%) missing valuesMissing
Response Type_Collect Sample has 1462 (2.0%) missing valuesMissing
Response Type_Cull has 1462 (2.0%) missing valuesMissing
Response Type_Destroy Animal has 1462 (2.0%) missing valuesMissing
Response Type_Disentangle has 1462 (2.0%) missing valuesMissing
Response Type_Dispatch other Agency has 1462 (2.0%) missing valuesMissing
Response Type_Disperse Wildlife Jam has 1462 (2.0%) missing valuesMissing
Response Type_Dispose Carcass has 1462 (2.0%) missing valuesMissing
Response Type_Ear Tag has 1462 (2.0%) missing valuesMissing
Response Type_Euthanize has 1462 (2.0%) missing valuesMissing
Response Type_Evacuate Visitor has 1462 (2.0%) missing valuesMissing
Response Type_Haze - Hard has 1462 (2.0%) missing valuesMissing
Response Type_Haze - Soft has 1462 (2.0%) missing valuesMissing
Response Type_Immobilize Animal has 1462 (2.0%) missing valuesMissing
Response Type_Inform Visitor has 1462 (2.0%) missing valuesMissing
Response Type_Infrastructure modification has 1462 (2.0%) missing valuesMissing
Response Type_Investigate Incident has 1462 (2.0%) missing valuesMissing
Response Type_Issue Prohibited Activity Order has 1462 (2.0%) missing valuesMissing
Response Type_Issue Restricted Activity Order has 1462 (2.0%) missing valuesMissing
Response Type_Issue Stop Work Order has 1462 (2.0%) missing valuesMissing
Response Type_Leave on Landscape has 1462 (2.0%) missing valuesMissing
Response Type_Mark - paint has 1462 (2.0%) missing valuesMissing
Response Type_Monitor - Camera has 1462 (2.0%) missing valuesMissing
Response Type_Monitor - patrol has 1462 (2.0%) missing valuesMissing
Response Type_Monitor - visitor and staff sighting has 1462 (2.0%) missing valuesMissing
Response Type_Necropsy has 1462 (2.0%) missing valuesMissing
Response Type_No response required has 1462 (2.0%) missing valuesMissing
Response Type_Not Applicable has 1462 (2.0%) missing valuesMissing
Response Type_Refer incident to other agency has 1462 (2.0%) missing valuesMissing
Response Type_Rehabilitate area has 1462 (2.0%) missing valuesMissing
Response Type_Relocate animal (s) has 1462 (2.0%) missing valuesMissing
Response Type_Request assistance - other Agency has 1462 (2.0%) missing valuesMissing
Response Type_Request assistance - police has 1462 (2.0%) missing valuesMissing
Response Type_Traffic control has 1462 (2.0%) missing valuesMissing
Response Type_Translocate has 1462 (2.0%) missing valuesMissing
Response Type_Trap or snare has 1462 (2.0%) missing valuesMissing
Response Type_Unable to respond has 1462 (2.0%) missing valuesMissing
Response Type_Warning signs has 1462 (2.0%) missing valuesMissing
Response Type_nan has 1462 (2.0%) missing valuesMissing
Total Staff Hours is highly skewed (γ1 = 93.3034933)Skewed
Sum of Number of Animals is highly skewed (γ1 = 82.97341938)Skewed
UniqueID is uniformly distributedUniform
Incident Number is uniformly distributedUniform
UniqueID has unique valuesUnique
Sum of Number of Animals has 1894 (2.6%) zerosZeros

Reproduction

Analysis started2023-03-19 01:14:06.160139
Analysis finished2023-03-19 01:17:31.541163
Duration3 minutes and 25.38 seconds
Software versionpandas-profiling v3.6.6
Download configurationconfig.json

Variables

UniqueID
Categorical

HIGH CARDINALITY  UNIFORM  UNIQUE 

Distinct73658
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1.1 MiB
BAN2010-0003.3
 
1
2019-HWC-0000-JASFU-1678.2
 
1
2019-HWC-0000-JASFU-1683.1
 
1
2019-HWC-0000-JASFU-1682.1
 
1
2019-HWC-0000-JASFU-1681.1
 
1
Other values (73653)
73653 

Length

Max length27
Median length26
Mean length20.493334
Min length13

Characters and Unicode

Total characters1509498
Distinct characters38
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique73658 ?
Unique (%)100.0%

Sample

1st rowBAN2010-0003.3
2nd rowBAN2010-0003.2
3rd rowBAN2010-0003.1
4th rowJNP2010-0011.1
5th rowJNP2010-0015.1

Common Values

ValueCountFrequency (%)
BAN2010-0003.3 1
 
< 0.1%
2019-HWC-0000-JASFU-1678.2 1
 
< 0.1%
2019-HWC-0000-JASFU-1683.1 1
 
< 0.1%
2019-HWC-0000-JASFU-1682.1 1
 
< 0.1%
2019-HWC-0000-JASFU-1681.1 1
 
< 0.1%
2019-HWC-0000-JASFU-1680.1 1
 
< 0.1%
2019-HWC-0000-JASFU-1679.1 1
 
< 0.1%
2019-HWC-0000-JASFU-1678.1 1
 
< 0.1%
2019-HWC-0000-JASFU-1677.1 1
 
< 0.1%
2019-HWC-0000-JASFU-1685.1 1
 
< 0.1%
Other values (73648) 73648
> 99.9%

Length

2023-03-18T21:17:31.624946image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
ban2010-0003.3 1
 
< 0.1%
pa2010-0001.1 1
 
< 0.1%
jnp2010-0023.1 1
 
< 0.1%
jnp2010-0016.1 1
 
< 0.1%
ll2010-000001.1 1
 
< 0.1%
ll2010-0004.1 1
 
< 0.1%
prn2010-0001.1 1
 
< 0.1%
ban2010-0009.1 1
 
< 0.1%
wl2010-0001.1 1
 
< 0.1%
jnp2010-0011.1 1
 
< 0.1%
Other values (73648) 73648
> 99.9%

Most occurring characters

ValueCountFrequency (%)
0 282280
18.7%
- 193803
12.8%
1 182309
12.1%
2 137605
 
9.1%
. 73655
 
4.9%
C 49023
 
3.2%
W 48721
 
3.2%
F 44422
 
2.9%
U 44005
 
2.9%
H 43985
 
2.9%
Other values (28) 409690
27.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 798855
52.9%
Uppercase Letter 443182
29.4%
Dash Punctuation 193803
 
12.8%
Other Punctuation 73655
 
4.9%
Lowercase Letter 3
 
< 0.1%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
C 49023
11.1%
W 48721
11.0%
F 44422
10.0%
U 44005
9.9%
H 43985
9.9%
A 42692
9.6%
N 36414
8.2%
J 25983
5.9%
B 25624
 
5.8%
S 17704
 
4.0%
Other values (13) 64609
14.6%
Decimal Number
ValueCountFrequency (%)
0 282280
35.3%
1 182309
22.8%
2 137605
17.2%
9 30145
 
3.8%
3 28836
 
3.6%
5 28310
 
3.5%
4 28205
 
3.5%
6 27597
 
3.5%
8 26878
 
3.4%
7 26690
 
3.3%
Lowercase Letter
ValueCountFrequency (%)
y 1
33.3%
n 1
33.3%
p 1
33.3%
Dash Punctuation
ValueCountFrequency (%)
- 193803
100.0%
Other Punctuation
ValueCountFrequency (%)
. 73655
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1066313
70.6%
Latin 443185
29.4%

Most frequent character per script

Latin
ValueCountFrequency (%)
C 49023
11.1%
W 48721
11.0%
F 44422
10.0%
U 44005
9.9%
H 43985
9.9%
A 42692
9.6%
N 36414
8.2%
J 25983
5.9%
B 25624
 
5.8%
S 17704
 
4.0%
Other values (16) 64612
14.6%
Common
ValueCountFrequency (%)
0 282280
26.5%
- 193803
18.2%
1 182309
17.1%
2 137605
12.9%
. 73655
 
6.9%
9 30145
 
2.8%
3 28836
 
2.7%
5 28310
 
2.7%
4 28205
 
2.6%
6 27597
 
2.6%
Other values (2) 53568
 
5.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1509498
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 282280
18.7%
- 193803
12.8%
1 182309
12.1%
2 137605
 
9.1%
. 73655
 
4.9%
C 49023
 
3.2%
W 48721
 
3.2%
F 44422
 
2.9%
U 44005
 
2.9%
H 43985
 
2.9%
Other values (28) 409690
27.1%

Incident Number
Categorical

HIGH CARDINALITY  UNIFORM 

Distinct64258
Distinct (%)87.2%
Missing0
Missing (%)0.0%
Memory size1.1 MiB
BAN2013-1151
 
11
2020-HWC-0000-JASFU-0005
 
7
EI2014-0110
 
6
2021-HWC-0000-JASFU-0210
 
6
2017-HWC-BANFU-0912
 
6
Other values (64253)
73622 

Length

Max length25
Median length24
Mean length18.493388
Min length11

Characters and Unicode

Total characters1362186
Distinct characters37
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique55344 ?
Unique (%)75.1%

Sample

1st rowBAN2010-0003
2nd rowBAN2010-0003
3rd rowBAN2010-0003
4th rowJNP2010-0011
5th rowJNP2010-0015

Common Values

ValueCountFrequency (%)
BAN2013-1151 11
 
< 0.1%
2020-HWC-0000-JASFU-0005 7
 
< 0.1%
EI2014-0110 6
 
< 0.1%
2021-HWC-0000-JASFU-0210 6
 
< 0.1%
2017-HWC-BANFU-0912 6
 
< 0.1%
BAN2015-0042 5
 
< 0.1%
2017-HWC-BANFU-0435 5
 
< 0.1%
2020-HWC-0735-YKLLFU-0344 5
 
< 0.1%
PP2010-00001 5
 
< 0.1%
PRN2011-0014 5
 
< 0.1%
Other values (64248) 73597
99.9%

Length

2023-03-18T21:17:31.733788image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
ban2013-1151 11
 
< 0.1%
2020-hwc-0000-jasfu-0005 7
 
< 0.1%
ei2014-0110 6
 
< 0.1%
2021-hwc-0000-jasfu-0210 6
 
< 0.1%
2017-hwc-banfu-0912 6
 
< 0.1%
2019-hwc-0069-cbcfu-0025 5
 
< 0.1%
pp2013-0026 5
 
< 0.1%
2020-hwc-0634-ykllfu-0001 5
 
< 0.1%
pa2013-0098 5
 
< 0.1%
2019-hwc-0393-snwtfu-0002 5
 
< 0.1%
Other values (64248) 73597
99.9%

Most occurring characters

ValueCountFrequency (%)
0 282279
20.7%
- 193803
14.2%
2 128691
 
9.4%
1 118051
 
8.7%
C 49023
 
3.6%
W 48721
 
3.6%
F 44422
 
3.3%
U 44005
 
3.2%
H 43985
 
3.2%
A 42692
 
3.1%
Other values (27) 366514
26.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 725198
53.2%
Uppercase Letter 443182
32.5%
Dash Punctuation 193803
 
14.2%
Lowercase Letter 3
 
< 0.1%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
C 49023
11.1%
W 48721
11.0%
F 44422
10.0%
U 44005
9.9%
H 43985
9.9%
A 42692
9.6%
N 36414
8.2%
J 25983
5.9%
B 25624
 
5.8%
S 17704
 
4.0%
Other values (13) 64609
14.6%
Decimal Number
ValueCountFrequency (%)
0 282279
38.9%
2 128691
17.7%
1 118051
16.3%
9 30144
 
4.2%
3 28434
 
3.9%
5 28294
 
3.9%
4 28148
 
3.9%
6 27592
 
3.8%
8 26877
 
3.7%
7 26688
 
3.7%
Lowercase Letter
ValueCountFrequency (%)
y 1
33.3%
n 1
33.3%
p 1
33.3%
Dash Punctuation
ValueCountFrequency (%)
- 193803
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 919001
67.5%
Latin 443185
32.5%

Most frequent character per script

Latin
ValueCountFrequency (%)
C 49023
11.1%
W 48721
11.0%
F 44422
10.0%
U 44005
9.9%
H 43985
9.9%
A 42692
9.6%
N 36414
8.2%
J 25983
5.9%
B 25624
 
5.8%
S 17704
 
4.0%
Other values (16) 64612
14.6%
Common
ValueCountFrequency (%)
0 282279
30.7%
- 193803
21.1%
2 128691
14.0%
1 118051
12.8%
9 30144
 
3.3%
3 28434
 
3.1%
5 28294
 
3.1%
4 28148
 
3.1%
6 27592
 
3.0%
8 26877
 
2.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1362186
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 282279
20.7%
- 193803
14.2%
2 128691
 
9.4%
1 118051
 
8.7%
C 49023
 
3.6%
W 48721
 
3.6%
F 44422
 
3.3%
U 44005
 
3.2%
H 43985
 
3.2%
A 42692
 
3.1%
Other values (27) 366514
26.9%

Incident Date
Categorical

Distinct4299
Distinct (%)5.8%
Missing0
Missing (%)0.0%
Memory size1.1 MiB
2021-05-26
 
96
2021-05-28
 
94
2021-06-14
 
90
2021-05-27
 
89
2021-06-12
 
89
Other values (4294)
73200 

Length

Max length10
Median length10
Mean length10
Min length10

Characters and Unicode

Total characters736580
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique202 ?
Unique (%)0.3%

Sample

1st row2010-01-01
2nd row2010-01-01
3rd row2010-01-01
4th row2010-01-01
5th row2010-01-01

Common Values

ValueCountFrequency (%)
2021-05-26 96
 
0.1%
2021-05-28 94
 
0.1%
2021-06-14 90
 
0.1%
2021-05-27 89
 
0.1%
2021-06-12 89
 
0.1%
2021-05-29 88
 
0.1%
2021-06-25 87
 
0.1%
2019-06-22 87
 
0.1%
2019-06-11 87
 
0.1%
2021-06-19 86
 
0.1%
Other values (4289) 72765
98.8%

Length

2023-03-18T21:17:31.830961image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
2021-05-26 96
 
0.1%
2021-05-28 94
 
0.1%
2021-06-14 90
 
0.1%
2021-05-27 89
 
0.1%
2021-06-12 89
 
0.1%
2021-05-29 88
 
0.1%
2021-06-25 87
 
0.1%
2019-06-22 87
 
0.1%
2019-06-11 87
 
0.1%
2021-06-19 86
 
0.1%
Other values (4289) 72765
98.8%

Most occurring characters

ValueCountFrequency (%)
0 184475
25.0%
- 147316
20.0%
2 132650
18.0%
1 114137
15.5%
7 27767
 
3.8%
6 26356
 
3.6%
9 26053
 
3.5%
8 25242
 
3.4%
5 21643
 
2.9%
3 16561
 
2.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 589264
80.0%
Dash Punctuation 147316
 
20.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 184475
31.3%
2 132650
22.5%
1 114137
19.4%
7 27767
 
4.7%
6 26356
 
4.5%
9 26053
 
4.4%
8 25242
 
4.3%
5 21643
 
3.7%
3 16561
 
2.8%
4 14380
 
2.4%
Dash Punctuation
ValueCountFrequency (%)
- 147316
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 736580
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 184475
25.0%
- 147316
20.0%
2 132650
18.0%
1 114137
15.5%
7 27767
 
3.8%
6 26356
 
3.6%
9 26053
 
3.5%
8 25242
 
3.4%
5 21643
 
2.9%
3 16561
 
2.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 736580
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 184475
25.0%
- 147316
20.0%
2 132650
18.0%
1 114137
15.5%
7 27767
 
3.8%
6 26356
 
3.6%
9 26053
 
3.5%
8 25242
 
3.4%
5 21643
 
2.9%
3 16561
 
2.2%

Field Unit
Categorical

Distinct19
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size1.1 MiB
Jasper Field Unit
25982 
Banff Field Unit
21581 
Lake Louise, Yoho and Kootenay Field Unit
9475 
Waterton Lakes Field Unit
4390 
Coastal British Columbia Field Unit
3439 
Other values (14)
8791 

Length

Max length42
Median length41
Mean length22.908971
Min length16

Characters and Unicode

Total characters1687429
Distinct characters43
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowBanff Field Unit
2nd rowBanff Field Unit
3rd rowBanff Field Unit
4th rowJasper Field Unit
5th rowJasper Field Unit

Common Values

ValueCountFrequency (%)
Jasper Field Unit 25982
35.3%
Banff Field Unit 21581
29.3%
Lake Louise, Yoho and Kootenay Field Unit 9475
 
12.9%
Waterton Lakes Field Unit 4390
 
6.0%
Coastal British Columbia Field Unit 3439
 
4.7%
Northern Prairies Field Unit 2700
 
3.7%
Mount Revelstoke and Glacier Field Unit 1920
 
2.6%
Eastern and Central Ontario Field Unit 1246
 
1.7%
Gaspesie Field Unit 586
 
0.8%
Saskatchewan South Field Unit 562
 
0.8%
Other values (9) 1777
 
2.4%

Length

2023-03-18T21:17:31.925543image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
unit 73658
25.8%
field 73658
25.8%
jasper 25982
 
9.1%
banff 21581
 
7.6%
and 12641
 
4.4%
lake 9475
 
3.3%
louise 9475
 
3.3%
yoho 9475
 
3.3%
kootenay 9475
 
3.3%
lakes 4390
 
1.5%
Other values (32) 35755
12.5%

Most occurring characters

ValueCountFrequency (%)
211907
12.6%
i 178187
 
10.6%
e 157228
 
9.3%
n 133334
 
7.9%
t 113654
 
6.7%
a 111171
 
6.6%
d 88085
 
5.2%
l 86379
 
5.1%
U 73658
 
4.4%
F 73658
 
4.4%
Other values (33) 460168
27.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 1193123
70.7%
Uppercase Letter 272924
 
16.2%
Space Separator 211907
 
12.6%
Other Punctuation 9475
 
0.6%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
i 178187
14.9%
e 157228
13.2%
n 133334
11.2%
t 113654
9.5%
a 111171
9.3%
d 88085
7.4%
l 86379
7.2%
o 69490
 
5.8%
s 56563
 
4.7%
r 53569
 
4.5%
Other values (11) 145463
12.2%
Uppercase Letter
ValueCountFrequency (%)
U 73658
27.0%
F 73658
27.0%
J 25982
 
9.5%
B 25220
 
9.2%
L 23340
 
8.6%
K 9475
 
3.5%
Y 9475
 
3.5%
C 8124
 
3.0%
W 4412
 
1.6%
N 3770
 
1.4%
Other values (10) 15810
 
5.8%
Space Separator
ValueCountFrequency (%)
211907
100.0%
Other Punctuation
ValueCountFrequency (%)
, 9475
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 1466047
86.9%
Common 221382
 
13.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
i 178187
12.2%
e 157228
10.7%
n 133334
 
9.1%
t 113654
 
7.8%
a 111171
 
7.6%
d 88085
 
6.0%
l 86379
 
5.9%
U 73658
 
5.0%
F 73658
 
5.0%
o 69490
 
4.7%
Other values (31) 381203
26.0%
Common
ValueCountFrequency (%)
211907
95.7%
, 9475
 
4.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1687429
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
211907
12.6%
i 178187
 
10.6%
e 157228
 
9.3%
n 133334
 
7.9%
t 113654
 
6.7%
a 111171
 
6.6%
d 88085
 
5.2%
l 86379
 
5.1%
U 73658
 
4.4%
F 73658
 
4.4%
Other values (33) 460168
27.3%
Distinct35
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size1.1 MiB
Banff National Park of Canada
27030 
Jasper National Park of Canada
25982 
Waterton Lakes National Park of Canada
4390 
Pacific Rim National Park Reserve of Canada
3439 
Kootenay National Park of Canada
 
2100
Other values (30)
10717 

Length

Max length61
Median length53
Mean length31.492642
Min length28

Characters and Unicode

Total characters2319685
Distinct characters46
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique5 ?
Unique (%)< 0.1%

Sample

1st rowBanff National Park of Canada
2nd rowBanff National Park of Canada
3rd rowBanff National Park of Canada
4th rowJasper National Park of Canada
5th rowJasper National Park of Canada

Common Values

ValueCountFrequency (%)
Banff National Park of Canada 27030
36.7%
Jasper National Park of Canada 25982
35.3%
Waterton Lakes National Park of Canada 4390
 
6.0%
Pacific Rim National Park Reserve of Canada 3439
 
4.7%
Kootenay National Park of Canada 2100
 
2.9%
Yoho National Park of Canada 1926
 
2.6%
Elk Island National Park of Canada 1481
 
2.0%
Glacier National Park of Canada 1344
 
1.8%
Prince Albert National Park of Canada 1219
 
1.7%
Georgian Bay Islands National Park of Canada 864
 
1.2%
Other values (25) 3883
 
5.3%

Length

2023-03-18T21:17:32.030003image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
national 73749
19.0%
of 73741
19.0%
canada 73651
19.0%
park 73555
19.0%
banff 27030
 
7.0%
jasper 25982
 
6.7%
waterton 4390
 
1.1%
lakes 4390
 
1.1%
reserve 3474
 
0.9%
pacific 3439
 
0.9%
Other values (49) 23993
 
6.2%

Most occurring characters

ValueCountFrequency (%)
a 518411
22.3%
313736
13.5%
n 189216
 
8.2%
o 165354
 
7.1%
f 131864
 
5.7%
r 115192
 
5.0%
i 90142
 
3.9%
t 87829
 
3.8%
l 83942
 
3.6%
k 80235
 
3.5%
Other values (36) 543764
23.4%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 1692377
73.0%
Space Separator 313736
 
13.5%
Uppercase Letter 313563
 
13.5%
Dash Punctuation 5
 
< 0.1%
Other Punctuation 4
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a 518411
30.6%
n 189216
 
11.2%
o 165354
 
9.8%
f 131864
 
7.8%
r 115192
 
6.8%
i 90142
 
5.3%
t 87829
 
5.2%
l 83942
 
5.0%
k 80235
 
4.7%
d 78293
 
4.6%
Other values (14) 151899
 
9.0%
Uppercase Letter
ValueCountFrequency (%)
P 79642
25.4%
N 74067
23.6%
C 73651
23.5%
B 28506
 
9.1%
J 25982
 
8.3%
R 7490
 
2.4%
W 4825
 
1.5%
L 4396
 
1.4%
I 2818
 
0.9%
G 2763
 
0.9%
Other values (9) 9423
 
3.0%
Space Separator
ValueCountFrequency (%)
313736
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 5
100.0%
Other Punctuation
ValueCountFrequency (%)
? 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 2005940
86.5%
Common 313745
 
13.5%

Most frequent character per script

Latin
ValueCountFrequency (%)
a 518411
25.8%
n 189216
 
9.4%
o 165354
 
8.2%
f 131864
 
6.6%
r 115192
 
5.7%
i 90142
 
4.5%
t 87829
 
4.4%
l 83942
 
4.2%
k 80235
 
4.0%
P 79642
 
4.0%
Other values (33) 464113
23.1%
Common
ValueCountFrequency (%)
313736
> 99.9%
- 5
 
< 0.1%
? 4
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2319681
> 99.9%
None 4
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
a 518411
22.3%
313736
13.5%
n 189216
 
8.2%
o 165354
 
7.1%
f 131864
 
5.7%
r 115192
 
5.0%
i 90142
 
3.9%
t 87829
 
3.8%
l 83942
 
3.6%
k 80235
 
3.5%
Other values (35) 543760
23.4%
None
ValueCountFrequency (%)
ú 4
100.0%

Incident Type
Categorical

Distinct9
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size1.1 MiB
Human Wildlife Interaction
48673 
Rescued/Recovered/Found Wildlife
13820 
Wildlife Sighting
 
3925
Management Intervention
 
1989
Highway Fence Intrusion
 
1396
Other values (4)
 
3855

Length

Max length32
Median length26
Mean length25.780133
Min length10

Characters and Unicode

Total characters1898913
Distinct characters31
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowHuman Wildlife Interaction
2nd rowHuman Wildlife Interaction
3rd rowHuman Wildlife Interaction
4th rowRescued/Recovered/Found Wildlife
5th rowAttractant

Common Values

ValueCountFrequency (%)
Human Wildlife Interaction 48673
66.1%
Rescued/Recovered/Found Wildlife 13820
 
18.8%
Wildlife Sighting 3925
 
5.3%
Management Intervention 1989
 
2.7%
Highway Fence Intrusion 1396
 
1.9%
Harassment 1353
 
1.8%
Attractant 1275
 
1.7%
Nuisance Wildlife 955
 
1.3%
Domestic Animal 272
 
0.4%

Length

2023-03-18T21:17:32.129322image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-03-18T21:17:32.259152image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
wildlife 67373
34.6%
human 48673
25.0%
interaction 48673
25.0%
rescued/recovered/found 13820
 
7.1%
sighting 3925
 
2.0%
management 1989
 
1.0%
intervention 1989
 
1.0%
highway 1396
 
0.7%
fence 1396
 
0.7%
intrusion 1396
 
0.7%
Other values (5) 4127
 
2.1%

Most occurring characters

ValueCountFrequency (%)
e 198474
 
10.5%
i 197549
 
10.4%
n 181752
 
9.6%
l 135018
 
7.1%
121099
 
6.4%
t 115359
 
6.1%
a 109203
 
5.8%
d 108833
 
5.7%
c 80211
 
4.2%
o 79970
 
4.2%
Other values (21) 571445
30.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 1527777
80.5%
Uppercase Letter 222397
 
11.7%
Space Separator 121099
 
6.4%
Other Punctuation 27640
 
1.5%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 198474
13.0%
i 197549
12.9%
n 181752
11.9%
l 135018
8.8%
t 115359
7.6%
a 109203
7.1%
d 108833
7.1%
c 80211
 
5.3%
o 79970
 
5.2%
u 78664
 
5.1%
Other values (9) 242744
15.9%
Uppercase Letter
ValueCountFrequency (%)
W 67373
30.3%
I 52058
23.4%
H 51422
23.1%
R 27640
12.4%
F 15216
 
6.8%
S 3925
 
1.8%
M 1989
 
0.9%
A 1547
 
0.7%
N 955
 
0.4%
D 272
 
0.1%
Space Separator
ValueCountFrequency (%)
121099
100.0%
Other Punctuation
ValueCountFrequency (%)
/ 27640
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 1750174
92.2%
Common 148739
 
7.8%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 198474
11.3%
i 197549
11.3%
n 181752
 
10.4%
l 135018
 
7.7%
t 115359
 
6.6%
a 109203
 
6.2%
d 108833
 
6.2%
c 80211
 
4.6%
o 79970
 
4.6%
u 78664
 
4.5%
Other values (19) 465141
26.6%
Common
ValueCountFrequency (%)
121099
81.4%
/ 27640
 
18.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1898913
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e 198474
 
10.5%
i 197549
 
10.4%
n 181752
 
9.6%
l 135018
 
7.1%
121099
 
6.4%
t 115359
 
6.1%
a 109203
 
5.8%
d 108833
 
5.7%
c 80211
 
4.2%
o 79970
 
4.2%
Other values (21) 571445
30.1%

Latitude Public
Real number (ℝ)

Distinct60194
Distinct (%)81.8%
Missing34
Missing (%)< 0.1%
Infinite0
Infinite (%)0.0%
Mean51.484498
Minimum41.902015
Maximum73.998028
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.1 MiB
2023-03-18T21:17:32.399395image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum41.902015
5-th percentile48.811123
Q151.168223
median51.286676
Q352.872448
95-th percentile53.193282
Maximum73.998028
Range32.096013
Interquartile range (IQR)1.7042253

Descriptive statistics

Standard deviation1.9002131
Coefficient of variation (CV)0.036908453
Kurtosis7.7743069
Mean51.484498
Median Absolute Deviation (MAD)1.5463275
Skewness-0.83089328
Sum3790494.6
Variance3.61081
MonotonicityNot monotonic
2023-03-18T21:17:32.515199image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
51.189384 11
 
< 0.1%
51.167511 9
 
< 0.1%
52.787584 7
 
< 0.1%
51.186665 7
 
< 0.1%
51.191362 6
 
< 0.1%
51.181433 6
 
< 0.1%
52.859852 6
 
< 0.1%
53.711632 6
 
< 0.1%
51.169038 6
 
< 0.1%
52.884987 6
 
< 0.1%
Other values (60184) 73554
99.9%
(Missing) 34
 
< 0.1%
ValueCountFrequency (%)
41.902015 1
< 0.1%
41.902586 1
< 0.1%
41.904603 1
< 0.1%
41.904769 1
< 0.1%
41.905485 1
< 0.1%
41.90787 1
< 0.1%
41.908166 1
< 0.1%
41.908198 1
< 0.1%
41.908328 1
< 0.1%
41.90867 1
< 0.1%
ValueCountFrequency (%)
73.998028 1
< 0.1%
69.235962 1
< 0.1%
69.234609 1
< 0.1%
69.234373 1
< 0.1%
69.226879 1
< 0.1%
69.223639 1
< 0.1%
69.223471 1
< 0.1%
69.219153 2
< 0.1%
69.214274 1
< 0.1%
69.176994 1
< 0.1%

Longitude Public
Real number (ℝ)

Distinct61241
Distinct (%)83.2%
Missing34
Missing (%)< 0.1%
Infinite0
Infinite (%)0.0%
Mean-114.77093
Minimum-140.29774
Maximum-52.637169
Zeros0
Zeros (%)0.0%
Negative73624
Negative (%)> 99.9%
Memory size1.1 MiB
2023-03-18T21:17:32.643899image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum-140.29774
5-th percentile-118.31809
Q1-118.06334
median-116.16563
Q3-115.55147
95-th percentile-106.07185
Maximum-52.637169
Range87.660569
Interquartile range (IQR)2.511872

Descriptive statistics

Standard deviation9.7848652
Coefficient of variation (CV)-0.085255606
Kurtosis18.465229
Mean-114.77093
Median Absolute Deviation (MAD)1.821913
Skewness4.1750789
Sum-8449895
Variance95.743587
MonotonicityNot monotonic
2023-03-18T21:17:32.759295image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
-115.527437 11
 
< 0.1%
-115.592653 7
 
< 0.1%
-118.077652 7
 
< 0.1%
-118.095825 7
 
< 0.1%
-115.604491 6
 
< 0.1%
-115.554429 6
 
< 0.1%
-118.109658 6
 
< 0.1%
-118.090641 6
 
< 0.1%
-115.588321 6
 
< 0.1%
-115.579766 6
 
< 0.1%
Other values (61231) 73556
99.9%
(Missing) 34
 
< 0.1%
ValueCountFrequency (%)
-140.297738 1
< 0.1%
-140.293959 1
< 0.1%
-140.293928 1
< 0.1%
-140.276639 1
< 0.1%
-140.191992 1
< 0.1%
-140.133746 1
< 0.1%
-140.130154 1
< 0.1%
-139.835416 1
< 0.1%
-139.828219 1
< 0.1%
-139.826535 1
< 0.1%
ValueCountFrequency (%)
-52.637169 1
< 0.1%
-52.665674 1
< 0.1%
-52.665765 1
< 0.1%
-52.670844 1
< 0.1%
-52.670923 1
< 0.1%
-52.672385 1
< 0.1%
-52.67523 1
< 0.1%
-52.675995 1
< 0.1%
-52.677084 1
< 0.1%
-52.677246 1
< 0.1%
Distinct2
Distinct (%)< 0.1%
Missing40
Missing (%)0.1%
Memory size719.3 KiB
True
72755 
False
 
863
(Missing)
 
40
ValueCountFrequency (%)
True 72755
98.8%
False 863
 
1.2%
(Missing) 40
 
0.1%
2023-03-18T21:17:32.868990image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Total Staff Involved
Real number (ℝ)

Distinct24
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.4777892
Minimum0
Maximum32
Zeros2
Zeros (%)< 0.1%
Negative0
Negative (%)0.0%
Memory size1.1 MiB
2023-03-18T21:17:32.965026image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q11
median1
Q32
95-th percentile3
Maximum32
Range32
Interquartile range (IQR)1

Descriptive statistics

Standard deviation1.0554122
Coefficient of variation (CV)0.71418319
Kurtosis61.041685
Mean1.4777892
Median Absolute Deviation (MAD)0
Skewness5.3765076
Sum108851
Variance1.113895
MonotonicityNot monotonic
2023-03-18T21:17:33.060547image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=24)
ValueCountFrequency (%)
1 52026
70.6%
2 14798
 
20.1%
3 3779
 
5.1%
4 1638
 
2.2%
5 647
 
0.9%
6 319
 
0.4%
7 144
 
0.2%
8 102
 
0.1%
9 63
 
0.1%
12 40
 
0.1%
Other values (14) 102
 
0.1%
ValueCountFrequency (%)
0 2
 
< 0.1%
1 52026
70.6%
2 14798
 
20.1%
3 3779
 
5.1%
4 1638
 
2.2%
5 647
 
0.9%
6 319
 
0.4%
7 144
 
0.2%
8 102
 
0.1%
9 63
 
0.1%
ValueCountFrequency (%)
32 1
 
< 0.1%
28 1
 
< 0.1%
24 5
< 0.1%
22 1
 
< 0.1%
19 2
 
< 0.1%
18 5
< 0.1%
17 1
 
< 0.1%
16 1
 
< 0.1%
15 9
< 0.1%
14 8
< 0.1%

Total Staff Hours
Real number (ℝ)

HIGH CORRELATION  SKEWED 

Distinct1027
Distinct (%)1.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.3310686
Minimum0
Maximum2400
Zeros23
Zeros (%)< 0.1%
Negative0
Negative (%)0.0%
Memory size1.1 MiB
2023-03-18T21:17:33.174500image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.25
Q10.5
median1
Q32
95-th percentile7
Maximum2400
Range2400
Interquartile range (IQR)1.5

Descriptive statistics

Standard deviation14.361819
Coefficient of variation (CV)6.1610453
Kurtosis12556.712
Mean2.3310686
Median Absolute Deviation (MAD)0.5
Skewness93.303493
Sum171701.85
Variance206.26185
MonotonicityNot monotonic
2023-03-18T21:17:33.297498image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 13934
18.9%
0.5 11589
15.7%
2 5899
 
8.0%
0.75 4585
 
6.2%
1.5 3732
 
5.1%
0.25 3246
 
4.4%
3 2986
 
4.1%
0.333333343 2736
 
3.7%
4 1767
 
2.4%
0.166666672 1681
 
2.3%
Other values (1017) 21503
29.2%
ValueCountFrequency (%)
0 23
 
< 0.1%
0.08 19
 
< 0.1%
0.083333336 1123
 
1.5%
0.1 1
 
< 0.1%
0.15 1
 
< 0.1%
0.16 52
 
0.1%
0.166666672 1681
2.3%
0.2 14
 
< 0.1%
0.24 2
 
< 0.1%
0.25 3246
4.4%
ValueCountFrequency (%)
2400 1
 
< 0.1%
1200 2
 
< 0.1%
783.25 5
< 0.1%
691.5 1
 
< 0.1%
435.8 1
 
< 0.1%
339 2
 
< 0.1%
274.92 1
 
< 0.1%
262.6666665 1
 
< 0.1%
256 1
 
< 0.1%
211 1
 
< 0.1%

Species Common Name
Categorical

HIGH CARDINALITY  IMBALANCE 

Distinct321
Distinct (%)0.4%
Missing3
Missing (%)< 0.1%
Memory size1.1 MiB
Black Bear
20898 
Elk
20433 
Grizzly Bear
9393 
Mule Deer
 
2081
White-tailed Deer
 
1766
Other values (316)
19084 

Length

Max length30
Median length29
Mean length8.1926549
Min length3

Characters and Unicode

Total characters603430
Distinct characters50
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique73 ?
Unique (%)0.1%

Sample

1st rowCoyote
2nd rowElk
3rd rowWolf
4th rowWhite-tailed Deer
5th rowNone

Common Values

ValueCountFrequency (%)
Black Bear 20898
28.4%
Elk 20433
27.7%
Grizzly Bear 9393
12.8%
Mule Deer 2081
 
2.8%
White-tailed Deer 1766
 
2.4%
None 1724
 
2.3%
Wolf 1617
 
2.2%
Bighorn Sheep 1353
 
1.8%
Coyote 1266
 
1.7%
Moose 1215
 
1.6%
Other values (311) 11909
16.2%

Length

2023-03-18T21:17:33.424846image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
bear 31009
26.4%
black 20912
17.8%
elk 20433
17.4%
grizzly 9393
 
8.0%
deer 4346
 
3.7%
mule 2081
 
1.8%
unknown 1996
 
1.7%
white-tailed 1766
 
1.5%
none 1724
 
1.5%
wolf 1617
 
1.4%
Other values (354) 22018
18.8%

Most occurring characters

ValueCountFrequency (%)
a 65094
10.8%
e 60528
 
10.0%
l 59994
 
9.9%
B 54508
 
9.0%
r 53823
 
8.9%
k 44378
 
7.4%
43640
 
7.2%
c 22745
 
3.8%
o 21115
 
3.5%
E 20619
 
3.4%
Other values (40) 156986
26.0%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 442225
73.3%
Uppercase Letter 115227
 
19.1%
Space Separator 43640
 
7.2%
Dash Punctuation 2201
 
0.4%
Other Punctuation 137
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a 65094
14.7%
e 60528
13.7%
l 59994
13.6%
r 53823
12.2%
k 44378
10.0%
c 22745
 
5.1%
o 21115
 
4.8%
i 19901
 
4.5%
z 18787
 
4.2%
n 15516
 
3.5%
Other values (15) 60344
13.6%
Uppercase Letter
ValueCountFrequency (%)
B 54508
47.3%
E 20619
 
17.9%
G 10745
 
9.3%
M 5329
 
4.6%
D 4858
 
4.2%
W 4387
 
3.8%
C 2996
 
2.6%
S 2729
 
2.4%
U 1996
 
1.7%
N 1877
 
1.6%
Other values (12) 5183
 
4.5%
Space Separator
ValueCountFrequency (%)
43640
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2201
100.0%
Other Punctuation
ValueCountFrequency (%)
' 137
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 557452
92.4%
Common 45978
 
7.6%

Most frequent character per script

Latin
ValueCountFrequency (%)
a 65094
11.7%
e 60528
10.9%
l 59994
10.8%
B 54508
9.8%
r 53823
 
9.7%
k 44378
 
8.0%
c 22745
 
4.1%
o 21115
 
3.8%
E 20619
 
3.7%
i 19901
 
3.6%
Other values (37) 134747
24.2%
Common
ValueCountFrequency (%)
43640
94.9%
- 2201
 
4.8%
' 137
 
0.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 603430
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
a 65094
10.8%
e 60528
 
10.0%
l 59994
 
9.9%
B 54508
 
9.0%
r 53823
 
8.9%
k 44378
 
7.4%
43640
 
7.2%
c 22745
 
3.8%
o 21115
 
3.5%
E 20619
 
3.4%
Other values (40) 156986
26.0%

Sum of Number of Animals
Real number (ℝ)

HIGH CORRELATION  SKEWED  ZEROS 

Distinct120
Distinct (%)0.2%
Missing3
Missing (%)< 0.1%
Infinite0
Infinite (%)0.0%
Mean2.7287761
Minimum0
Maximum2000
Zeros1894
Zeros (%)2.6%
Negative0
Negative (%)0.0%
Memory size1.1 MiB
2023-03-18T21:17:33.542597image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q11
median1
Q31
95-th percentile9
Maximum2000
Range2000
Interquartile range (IQR)0

Descriptive statistics

Standard deviation14.389458
Coefficient of variation (CV)5.2732278
Kurtosis10553.757
Mean2.7287761
Median Absolute Deviation (MAD)0
Skewness82.973419
Sum200988
Variance207.05649
MonotonicityNot monotonic
2023-03-18T21:17:33.666598image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 55531
75.4%
2 6290
 
8.5%
3 2910
 
4.0%
0 1894
 
2.6%
4 1232
 
1.7%
5 729
 
1.0%
6 590
 
0.8%
8 394
 
0.5%
7 371
 
0.5%
10 370
 
0.5%
Other values (110) 3344
 
4.5%
ValueCountFrequency (%)
0 1894
 
2.6%
1 55531
75.4%
2 6290
 
8.5%
3 2910
 
4.0%
4 1232
 
1.7%
5 729
 
1.0%
6 590
 
0.8%
7 371
 
0.5%
8 394
 
0.5%
9 248
 
0.3%
ValueCountFrequency (%)
2000 2
 
< 0.1%
1000 1
 
< 0.1%
600 2
 
< 0.1%
500 3
 
< 0.1%
300 3
 
< 0.1%
252 1
 
< 0.1%
240 2
 
< 0.1%
228 1
 
< 0.1%
220 1
 
< 0.1%
200 8
< 0.1%

Animal Health Status
Categorical

HIGH CORRELATION  MISSING 

Distinct9
Distinct (%)< 0.1%
Missing32173
Missing (%)43.7%
Memory size1.1 MiB
Healthy
25719 
Dead
7572 
Not Located
5230 
Injured
 
1471
Unknown
 
1273
Other values (4)
 
220

Length

Max length14
Median length7
Mean length6.9496927
Min length4

Characters and Unicode

Total characters288308
Distinct characters28
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowHealthy
2nd rowDead
3rd rowNot Located
4th rowDead
5th rowNot Located

Common Values

ValueCountFrequency (%)
Healthy 25719
34.9%
Dead 7572
 
10.3%
Not Located 5230
 
7.1%
Injured 1471
 
2.0%
Unknown 1273
 
1.7%
Other 85
 
0.1%
Sick 76
 
0.1%
Orphaned 51
 
0.1%
Not Applicable 8
 
< 0.1%
(Missing) 32173
43.7%

Length

2023-03-18T21:17:33.781797image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-03-18T21:17:33.896332image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
healthy 25719
55.0%
dead 7572
 
16.2%
not 5238
 
11.2%
located 5230
 
11.2%
injured 1471
 
3.1%
unknown 1273
 
2.7%
other 85
 
0.2%
sick 76
 
0.2%
orphaned 51
 
0.1%
applicable 8
 
< 0.1%

Most occurring characters

ValueCountFrequency (%)
e 40136
13.9%
a 38580
13.4%
t 36272
12.6%
h 25855
9.0%
l 25735
8.9%
H 25719
8.9%
y 25719
8.9%
d 14324
 
5.0%
o 11741
 
4.1%
D 7572
 
2.6%
Other values (18) 36655
12.7%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 236347
82.0%
Uppercase Letter 46723
 
16.2%
Space Separator 5238
 
1.8%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 40136
17.0%
a 38580
16.3%
t 36272
15.3%
h 25855
10.9%
l 25735
10.9%
y 25719
10.9%
d 14324
 
6.1%
o 11741
 
5.0%
n 5341
 
2.3%
c 5314
 
2.2%
Other values (8) 7330
 
3.1%
Uppercase Letter
ValueCountFrequency (%)
H 25719
55.0%
D 7572
 
16.2%
N 5238
 
11.2%
L 5230
 
11.2%
I 1471
 
3.1%
U 1273
 
2.7%
O 136
 
0.3%
S 76
 
0.2%
A 8
 
< 0.1%
Space Separator
ValueCountFrequency (%)
5238
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 283070
98.2%
Common 5238
 
1.8%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 40136
14.2%
a 38580
13.6%
t 36272
12.8%
h 25855
9.1%
l 25735
9.1%
H 25719
9.1%
y 25719
9.1%
d 14324
 
5.1%
o 11741
 
4.1%
D 7572
 
2.7%
Other values (17) 31417
11.1%
Common
ValueCountFrequency (%)
5238
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 288308
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e 40136
13.9%
a 38580
13.4%
t 36272
12.6%
h 25855
9.0%
l 25735
8.9%
H 25719
8.9%
y 25719
8.9%
d 14324
 
5.0%
o 11741
 
4.1%
D 7572
 
2.6%
Other values (18) 36655
12.7%

Cause of Animal Health Status
Categorical

HIGH CORRELATION  MISSING 

Distinct17
Distinct (%)0.1%
Missing60461
Missing (%)82.1%
Memory size1.1 MiB
Collision
5752 
Unknown
2888 
Entangle-Entrapment
2102 
Predation
854 
Management Destruction
 
523
Other values (12)
1078 

Length

Max length33
Median length9
Mean length10.899826
Min length5

Characters and Unicode

Total characters143845
Distinct characters39
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowPredation
2nd rowCollision
3rd rowCollision
4th rowCollision
5th rowCollision

Common Values

ValueCountFrequency (%)
Collision 5752
 
7.8%
Unknown 2888
 
3.9%
Entangle-Entrapment 2102
 
2.9%
Predation 854
 
1.2%
Management Destruction 523
 
0.7%
Other 323
 
0.4%
Natural Mortality 222
 
0.3%
Disease 119
 
0.2%
Not Applicable 117
 
0.2%
Hunting - Trapping 112
 
0.2%
Other values (7) 185
 
0.3%
(Missing) 60461
82.1%

Length

2023-03-18T21:17:34.012224image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
collision 5752
40.0%
unknown 2888
20.1%
entangle-entrapment 2102
 
14.6%
predation 854
 
5.9%
management 523
 
3.6%
destruction 523
 
3.6%
other 323
 
2.2%
natural 222
 
1.5%
mortality 222
 
1.5%
123
 
0.9%
Other values (17) 861
 
6.0%

Most occurring characters

ValueCountFrequency (%)
n 25834
18.0%
o 16366
11.4%
l 14295
9.9%
i 13887
9.7%
t 10218
 
7.1%
e 7544
 
5.2%
a 7278
 
5.1%
s 6589
 
4.6%
C 5811
 
4.0%
r 4533
 
3.2%
Other values (29) 31490
21.9%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 124052
86.2%
Uppercase Letter 16361
 
11.4%
Dash Punctuation 2225
 
1.5%
Space Separator 1196
 
0.8%
Other Punctuation 11
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
n 25834
20.8%
o 16366
13.2%
l 14295
11.5%
i 13887
11.2%
t 10218
 
8.2%
e 7544
 
6.1%
a 7278
 
5.9%
s 6589
 
5.3%
r 4533
 
3.7%
w 2937
 
2.4%
Other values (12) 14571
11.7%
Uppercase Letter
ValueCountFrequency (%)
C 5811
35.5%
E 4204
25.7%
U 2888
17.7%
P 886
 
5.4%
M 745
 
4.6%
D 702
 
4.3%
N 339
 
2.1%
O 323
 
2.0%
H 119
 
0.7%
A 117
 
0.7%
Other values (4) 227
 
1.4%
Dash Punctuation
ValueCountFrequency (%)
- 2225
100.0%
Space Separator
ValueCountFrequency (%)
1196
100.0%
Other Punctuation
ValueCountFrequency (%)
/ 11
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 140413
97.6%
Common 3432
 
2.4%

Most frequent character per script

Latin
ValueCountFrequency (%)
n 25834
18.4%
o 16366
11.7%
l 14295
10.2%
i 13887
9.9%
t 10218
 
7.3%
e 7544
 
5.4%
a 7278
 
5.2%
s 6589
 
4.7%
C 5811
 
4.1%
r 4533
 
3.2%
Other values (26) 28058
20.0%
Common
ValueCountFrequency (%)
- 2225
64.8%
1196
34.8%
/ 11
 
0.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 143845
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
n 25834
18.0%
o 16366
11.4%
l 14295
9.9%
i 13887
9.7%
t 10218
 
7.1%
e 7544
 
5.2%
a 7278
 
5.1%
s 6589
 
4.6%
C 5811
 
4.0%
r 4533
 
3.2%
Other values (29) 31490
21.9%

Animal Behaviour
Categorical

HIGH CORRELATION  MISSING 

Distinct22
Distinct (%)< 0.1%
Missing27983
Missing (%)38.0%
Memory size1.1 MiB
Presence - Wildlife Exclusion Zones
17003 
Indifferent to People/Vehicles
15854 
Avoidance
3327 
Bluff Charge
 
1648
Contact-Property
 
1200
Other values (17)
6643 

Length

Max length35
Median length34
Mean length27.114833
Min length4

Characters and Unicode

Total characters1238470
Distinct characters43
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowAvoidance
2nd rowPhysical or Aggressive Display
3rd rowContact-Property
4th rowIndifferent to People/Vehicles
5th rowCurious Approach

Common Values

ValueCountFrequency (%)
Presence - Wildlife Exclusion Zones 17003
23.1%
Indifferent to People/Vehicles 15854
21.5%
Avoidance 3327
 
4.5%
Bluff Charge 1648
 
2.2%
Contact-Property 1200
 
1.6%
Not Applicable 1175
 
1.6%
Curious Approach 918
 
1.2%
Physical or Aggressive Display 845
 
1.1%
Unknown 722
 
1.0%
Unaware 637
 
0.9%
Other values (12) 2346
 
3.2%
(Missing) 27983
38.0%

Length

2023-03-18T21:17:34.115725image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
presence 17003
11.1%
exclusion 17003
11.1%
zones 17003
11.1%
17003
11.1%
wildlife 17003
11.1%
to 16256
10.6%
indifferent 15854
10.3%
people/vehicles 15854
10.3%
avoidance 3327
 
2.2%
bluff 1648
 
1.1%
Other values (28) 15673
10.2%

Most occurring characters

ValueCountFrequency (%)
e 193071
15.6%
107952
 
8.7%
i 92805
 
7.5%
n 92217
 
7.4%
l 89856
 
7.3%
o 78709
 
6.4%
s 72381
 
5.8%
c 58148
 
4.7%
f 52409
 
4.2%
r 43228
 
3.5%
Other values (33) 357694
28.9%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 958856
77.4%
Uppercase Letter 135857
 
11.0%
Space Separator 107952
 
8.7%
Dash Punctuation 18689
 
1.5%
Other Punctuation 15854
 
1.3%
Open Punctuation 631
 
0.1%
Close Punctuation 631
 
0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 193071
20.1%
i 92805
9.7%
n 92217
9.6%
l 89856
9.4%
o 78709
8.2%
s 72381
 
7.5%
c 58148
 
6.1%
f 52409
 
5.5%
r 43228
 
4.5%
t 38776
 
4.0%
Other values (13) 147256
15.4%
Uppercase Letter
ValueCountFrequency (%)
P 35187
25.9%
E 17232
12.7%
Z 17003
12.5%
W 17003
12.5%
V 16059
11.8%
I 15945
11.7%
A 6293
 
4.6%
C 4521
 
3.3%
U 1761
 
1.3%
B 1648
 
1.2%
Other values (5) 3205
 
2.4%
Space Separator
ValueCountFrequency (%)
107952
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 18689
100.0%
Other Punctuation
ValueCountFrequency (%)
/ 15854
100.0%
Open Punctuation
ValueCountFrequency (%)
( 631
100.0%
Close Punctuation
ValueCountFrequency (%)
) 631
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 1094713
88.4%
Common 143757
 
11.6%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 193071
17.6%
i 92805
 
8.5%
n 92217
 
8.4%
l 89856
 
8.2%
o 78709
 
7.2%
s 72381
 
6.6%
c 58148
 
5.3%
f 52409
 
4.8%
r 43228
 
3.9%
t 38776
 
3.5%
Other values (28) 283113
25.9%
Common
ValueCountFrequency (%)
107952
75.1%
- 18689
 
13.0%
/ 15854
 
11.0%
( 631
 
0.4%
) 631
 
0.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1238470
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e 193071
15.6%
107952
 
8.7%
i 92805
 
7.5%
n 92217
 
7.4%
l 89856
 
7.3%
o 78709
 
6.4%
s 72381
 
5.8%
c 58148
 
4.7%
f 52409
 
4.2%
r 43228
 
3.5%
Other values (33) 357694
28.9%

Reason for Animal Behaviour
Categorical

HIGH CORRELATION  MISSING 

Distinct16
Distinct (%)0.1%
Missing47521
Missing (%)64.5%
Memory size1.1 MiB
Habituation
15559 
Unknown
2745 
Defence of Young
 
1306
Not Applicable
 
1288
Stress
 
1165
Other values (11)
4074 

Length

Max length27
Median length11
Mean length11.295405
Min length6

Characters and Unicode

Total characters295228
Distinct characters34
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowSurprise
2nd rowUnknown
3rd rowDefence of Space
4th rowHabituation
5th rowHabituation

Common Values

ValueCountFrequency (%)
Habituation 15559
 
21.1%
Unknown 2745
 
3.7%
Defence of Young 1306
 
1.8%
Not Applicable 1288
 
1.7%
Stress 1165
 
1.6%
Food Reward 1024
 
1.4%
Food Conditioned 811
 
1.1%
Defence of Mate 496
 
0.7%
Defence of Space 460
 
0.6%
Surprise 433
 
0.6%
Other values (6) 850
 
1.2%
(Missing) 47521
64.5%

Length

2023-03-18T21:17:34.218770image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
habituation 15559
44.0%
of 2825
 
8.0%
unknown 2745
 
7.8%
defence 2442
 
6.9%
food 2015
 
5.7%
young 1306
 
3.7%
not 1288
 
3.6%
applicable 1288
 
3.6%
stress 1165
 
3.3%
reward 1024
 
2.9%
Other values (12) 3732
 
10.5%

Most occurring characters

ValueCountFrequency (%)
t 35540
12.0%
i 35391
12.0%
a 35182
11.9%
o 30103
10.2%
n 30056
10.2%
u 17298
 
5.9%
b 16847
 
5.7%
H 15559
 
5.3%
e 14926
 
5.1%
9252
 
3.1%
Other values (24) 55074
18.7%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 253412
85.8%
Uppercase Letter 32564
 
11.0%
Space Separator 9252
 
3.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
t 35540
14.0%
i 35391
14.0%
a 35182
13.9%
o 30103
11.9%
n 30056
11.9%
u 17298
6.8%
b 16847
6.6%
e 14926
5.9%
f 5267
 
2.1%
c 5052
 
2.0%
Other values (11) 27750
11.0%
Uppercase Letter
ValueCountFrequency (%)
H 15559
47.8%
D 2863
 
8.8%
U 2745
 
8.4%
S 2088
 
6.4%
F 2015
 
6.2%
A 1767
 
5.4%
Y 1306
 
4.0%
N 1288
 
4.0%
R 1024
 
3.1%
C 811
 
2.5%
Other values (2) 1098
 
3.4%
Space Separator
ValueCountFrequency (%)
9252
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 285976
96.9%
Common 9252
 
3.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
t 35540
12.4%
i 35391
12.4%
a 35182
12.3%
o 30103
10.5%
n 30056
10.5%
u 17298
 
6.0%
b 16847
 
5.9%
H 15559
 
5.4%
e 14926
 
5.2%
f 5267
 
1.8%
Other values (23) 49807
17.4%
Common
ValueCountFrequency (%)
9252
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 295228
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
t 35540
12.0%
i 35391
12.0%
a 35182
11.9%
o 30103
10.2%
n 30056
10.2%
u 17298
 
5.9%
b 16847
 
5.7%
H 15559
 
5.3%
e 14926
 
5.1%
9252
 
3.1%
Other values (24) 55074
18.7%

Animal Attractant
Categorical

HIGH CORRELATION  MISSING 

Distinct19
Distinct (%)0.1%
Missing48864
Missing (%)66.3%
Memory size1.1 MiB
Vegetation (natural)
9661 
Unknown
3084 
Domestic grass
1923 
Human food
1746 
Berries (natural)
1485 
Other values (14)
6895 

Length

Max length27
Median length21
Mean length15.441841
Min length4

Characters and Unicode

Total characters382865
Distinct characters40
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowPrey animal (natural)
2nd rowPrey animal (natural)
3rd rowGrain
4th rowUnknown
5th rowHuman food

Common Values

ValueCountFrequency (%)
Vegetation (natural) 9661
 
13.1%
Unknown 3084
 
4.2%
Domestic grass 1923
 
2.6%
Human food 1746
 
2.4%
Berries (natural) 1485
 
2.0%
Fruit tree, shrub or garden 1446
 
2.0%
Grain 1237
 
1.7%
Not Applicable 1103
 
1.5%
Garbage 777
 
1.1%
Domestic Animal 686
 
0.9%
Other values (9) 1646
 
2.2%
(Missing) 48864
66.3%

Length

2023-03-18T21:17:34.313528image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
natural 11826
24.1%
vegetation 9661
19.7%
unknown 3084
 
6.3%
domestic 2609
 
5.3%
grass 1923
 
3.9%
human 1746
 
3.6%
food 1746
 
3.6%
berries 1485
 
3.0%
fruit 1446
 
3.0%
tree 1446
 
3.0%
Other values (21) 11999
24.5%

Most occurring characters

ValueCountFrequency (%)
a 45507
11.9%
t 38311
 
10.0%
n 36940
 
9.6%
e 32166
 
8.4%
r 27459
 
7.2%
24177
 
6.3%
o 22126
 
5.8%
i 19450
 
5.1%
u 16562
 
4.3%
l 15834
 
4.1%
Other values (30) 104333
27.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 306920
80.2%
Uppercase Letter 26670
 
7.0%
Space Separator 24177
 
6.3%
Open Punctuation 11826
 
3.1%
Close Punctuation 11826
 
3.1%
Other Punctuation 1446
 
0.4%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a 45507
14.8%
t 38311
12.5%
n 36940
12.0%
e 32166
10.5%
r 27459
8.9%
o 22126
7.2%
i 19450
6.3%
u 16562
 
5.4%
l 15834
 
5.2%
g 13807
 
4.5%
Other values (11) 38758
12.6%
Uppercase Letter
ValueCountFrequency (%)
V 9661
36.2%
U 3084
 
11.6%
D 2609
 
9.8%
G 2014
 
7.6%
A 1789
 
6.7%
H 1746
 
6.5%
F 1496
 
5.6%
B 1485
 
5.6%
N 1103
 
4.1%
P 729
 
2.7%
Other values (5) 954
 
3.6%
Space Separator
ValueCountFrequency (%)
24177
100.0%
Open Punctuation
ValueCountFrequency (%)
( 11826
100.0%
Close Punctuation
ValueCountFrequency (%)
) 11826
100.0%
Other Punctuation
ValueCountFrequency (%)
, 1446
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 333590
87.1%
Common 49275
 
12.9%

Most frequent character per script

Latin
ValueCountFrequency (%)
a 45507
13.6%
t 38311
11.5%
n 36940
11.1%
e 32166
9.6%
r 27459
8.2%
o 22126
 
6.6%
i 19450
 
5.8%
u 16562
 
5.0%
l 15834
 
4.7%
g 13807
 
4.1%
Other values (26) 65428
19.6%
Common
ValueCountFrequency (%)
24177
49.1%
( 11826
24.0%
) 11826
24.0%
, 1446
 
2.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 382865
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
a 45507
11.9%
t 38311
 
10.0%
n 36940
 
9.6%
e 32166
 
8.4%
r 27459
 
7.2%
24177
 
6.3%
o 22126
 
5.8%
i 19450
 
5.1%
u 16562
 
4.3%
l 15834
 
4.1%
Other values (30) 104333
27.3%

Deterrents Used
Categorical

HIGH CORRELATION  MISSING 

Distinct25
Distinct (%)0.1%
Missing54118
Missing (%)73.5%
Memory size1.1 MiB
Noise - Voice
2474 
Impact - Chalkball
2224 
Presence of Officer/Person
2222 
Not Applicable
2217 
Non-impact - Chalkball
1516 
Other values (20)
8887 

Length

Max length26
Median length22
Mean length16.554452
Min length4

Characters and Unicode

Total characters323474
Distinct characters39
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowPresence of Officer/Person
2nd rowLethal Round - Rimfire
3rd rowPresence of Officer/Person
4th rowLethal Round - Centrefire
5th rowNone

Common Values

ValueCountFrequency (%)
Noise - Voice 2474
 
3.4%
Impact - Chalkball 2224
 
3.0%
Presence of Officer/Person 2222
 
3.0%
Not Applicable 2217
 
3.0%
Non-impact - Chalkball 1516
 
2.1%
None 1392
 
1.9%
Unknown 1094
 
1.5%
Visual - Flagging or stick 1032
 
1.4%
Noise - Banger or Screamer 815
 
1.1%
Noise - Horn 785
 
1.1%
Other values (15) 3769
 
5.1%
(Missing) 54118
73.5%

Length

2023-03-18T21:17:34.410987image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
11273
20.6%
noise 4981
 
9.1%
chalkball 3740
 
6.8%
impact 2898
 
5.3%
presence 2840
 
5.2%
of 2840
 
5.2%
voice 2474
 
4.5%
officer/person 2222
 
4.1%
applicable 2217
 
4.1%
not 2217
 
4.1%
Other values (27) 16952
31.0%

Most occurring characters

ValueCountFrequency (%)
35114
 
10.9%
e 30765
 
9.5%
o 22811
 
7.1%
l 20182
 
6.2%
a 20041
 
6.2%
i 18333
 
5.7%
c 16692
 
5.2%
n 16590
 
5.1%
r 14383
 
4.4%
- 12796
 
4.0%
Other values (29) 115767
35.8%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 233458
72.2%
Uppercase Letter 39884
 
12.3%
Space Separator 35114
 
10.9%
Dash Punctuation 12796
 
4.0%
Other Punctuation 2222
 
0.7%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 30765
13.2%
o 22811
9.8%
l 20182
 
8.6%
a 20041
 
8.6%
i 18333
 
7.9%
c 16692
 
7.1%
n 16590
 
7.1%
r 14383
 
6.2%
s 12107
 
5.2%
t 10021
 
4.3%
Other values (12) 51533
22.1%
Uppercase Letter
ValueCountFrequency (%)
N 10113
25.4%
P 5298
13.3%
V 4124
10.3%
C 4107
10.3%
I 2898
 
7.3%
O 2808
 
7.0%
A 2217
 
5.6%
S 1816
 
4.6%
B 1418
 
3.6%
R 1335
 
3.3%
Other values (4) 3750
 
9.4%
Space Separator
ValueCountFrequency (%)
35114
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 12796
100.0%
Other Punctuation
ValueCountFrequency (%)
/ 2222
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 273342
84.5%
Common 50132
 
15.5%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 30765
 
11.3%
o 22811
 
8.3%
l 20182
 
7.4%
a 20041
 
7.3%
i 18333
 
6.7%
c 16692
 
6.1%
n 16590
 
6.1%
r 14383
 
5.3%
s 12107
 
4.4%
N 10113
 
3.7%
Other values (26) 91325
33.4%
Common
ValueCountFrequency (%)
35114
70.0%
- 12796
 
25.5%
/ 2222
 
4.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 323474
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
35114
 
10.9%
e 30765
 
9.5%
o 22811
 
7.1%
l 20182
 
6.2%
a 20041
 
6.2%
i 18333
 
5.7%
c 16692
 
5.2%
n 16590
 
5.1%
r 14383
 
4.4%
- 12796
 
4.0%
Other values (29) 115767
35.8%

Animal Response to Deterrents
Categorical

HIGH CORRELATION  MISSING 

Distinct10
Distinct (%)0.1%
Missing63156
Missing (%)85.7%
Memory size1.1 MiB
Retreat - Run
4686 
Retreat - Walk
3191 
Not Applicable
1842 
Indifferent
 
421
Unknown
 
182
Other values (5)
 
180

Length

Max length16
Median length14
Mean length13.17968
Min length5

Characters and Unicode

Total characters138413
Distinct characters29
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowRetreat - Run
2nd rowRetreat - Walk
3rd rowRetreat - Walk
4th rowRetreat - Walk
5th rowRetreat - Walk

Common Values

ValueCountFrequency (%)
Retreat - Run 4686
 
6.4%
Retreat - Walk 3191
 
4.3%
Not Applicable 1842
 
2.5%
Indifferent 421
 
0.6%
Unknown 182
 
0.2%
Other 77
 
0.1%
Alert 42
 
0.1%
Unaware 27
 
< 0.1%
Charge 20
 
< 0.1%
Curious Approach 14
 
< 0.1%
(Missing) 63156
85.7%

Length

2023-03-18T21:17:34.504779image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-03-18T21:17:34.614846image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
retreat 7877
28.0%
7877
28.0%
run 4686
16.7%
walk 3191
11.4%
not 1842
 
6.6%
applicable 1842
 
6.6%
indifferent 421
 
1.5%
unknown 182
 
0.6%
other 77
 
0.3%
alert 42
 
0.1%
Other values (4) 75
 
0.3%

Most occurring characters

ValueCountFrequency (%)
e 18604
13.4%
t 18136
13.1%
17610
12.7%
a 12998
9.4%
R 12563
9.1%
r 8492
 
6.1%
- 7877
 
5.7%
l 6917
 
5.0%
n 6101
 
4.4%
u 4714
 
3.4%
Other values (19) 24401
17.6%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 92691
67.0%
Uppercase Letter 20235
 
14.6%
Space Separator 17610
 
12.7%
Dash Punctuation 7877
 
5.7%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 18604
20.1%
t 18136
19.6%
a 12998
14.0%
r 8492
9.2%
l 6917
 
7.5%
n 6101
 
6.6%
u 4714
 
5.1%
p 3712
 
4.0%
k 3373
 
3.6%
i 2277
 
2.5%
Other values (9) 7367
 
7.9%
Uppercase Letter
ValueCountFrequency (%)
R 12563
62.1%
W 3191
 
15.8%
A 1898
 
9.4%
N 1842
 
9.1%
I 421
 
2.1%
U 209
 
1.0%
O 77
 
0.4%
C 34
 
0.2%
Space Separator
ValueCountFrequency (%)
17610
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 7877
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 112926
81.6%
Common 25487
 
18.4%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 18604
16.5%
t 18136
16.1%
a 12998
11.5%
R 12563
11.1%
r 8492
7.5%
l 6917
 
6.1%
n 6101
 
5.4%
u 4714
 
4.2%
p 3712
 
3.3%
k 3373
 
3.0%
Other values (17) 17316
15.3%
Common
ValueCountFrequency (%)
17610
69.1%
- 7877
30.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 138413
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e 18604
13.4%
t 18136
13.1%
17610
12.7%
a 12998
9.4%
R 12563
9.1%
r 8492
 
6.1%
- 7877
 
5.7%
l 6917
 
5.0%
n 6101
 
4.4%
u 4714
 
3.4%
Other values (19) 24401
17.6%
Distinct2
Distinct (%)< 0.1%
Missing2
Missing (%)< 0.1%
Memory size1.1 MiB
0.0
73132 
1.0
 
524

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters220968
Distinct characters3
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
0.0 73132
99.3%
1.0 524
 
0.7%
(Missing) 2
 
< 0.1%

Length

2023-03-18T21:17:34.729424image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-03-18T21:17:34.821634image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
0.0 73132
99.3%
1.0 524
 
0.7%

Most occurring characters

ValueCountFrequency (%)
0 146788
66.4%
. 73656
33.3%
1 524
 
0.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 147312
66.7%
Other Punctuation 73656
33.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 146788
99.6%
1 524
 
0.4%
Other Punctuation
ValueCountFrequency (%)
. 73656
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 220968
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 146788
66.4%
. 73656
33.3%
1 524
 
0.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 220968
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 146788
66.4%
. 73656
33.3%
1 524
 
0.2%
Distinct2
Distinct (%)< 0.1%
Missing2
Missing (%)< 0.1%
Memory size1.1 MiB
0.0
73033 
1.0
 
623

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters220968
Distinct characters3
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
0.0 73033
99.2%
1.0 623
 
0.8%
(Missing) 2
 
< 0.1%

Length

2023-03-18T21:17:34.900547image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-03-18T21:17:34.993018image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
0.0 73033
99.2%
1.0 623
 
0.8%

Most occurring characters

ValueCountFrequency (%)
0 146689
66.4%
. 73656
33.3%
1 623
 
0.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 147312
66.7%
Other Punctuation 73656
33.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 146689
99.6%
1 623
 
0.4%
Other Punctuation
ValueCountFrequency (%)
. 73656
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 220968
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 146689
66.4%
. 73656
33.3%
1 623
 
0.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 220968
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 146689
66.4%
. 73656
33.3%
1 623
 
0.3%
Distinct2
Distinct (%)< 0.1%
Missing2
Missing (%)< 0.1%
Memory size1.1 MiB
0.0
73623 
1.0
 
33

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters220968
Distinct characters3
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
0.0 73623
> 99.9%
1.0 33
 
< 0.1%
(Missing) 2
 
< 0.1%

Length

2023-03-18T21:17:35.074780image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-03-18T21:17:35.166663image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
0.0 73623
> 99.9%
1.0 33
 
< 0.1%

Most occurring characters

ValueCountFrequency (%)
0 147279
66.7%
. 73656
33.3%
1 33
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 147312
66.7%
Other Punctuation 73656
33.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 147279
> 99.9%
1 33
 
< 0.1%
Other Punctuation
ValueCountFrequency (%)
. 73656
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 220968
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 147279
66.7%
. 73656
33.3%
1 33
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 220968
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 147279
66.7%
. 73656
33.3%
1 33
 
< 0.1%

Activity Type_Boating - Commercial
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing2
Missing (%)< 0.1%
Memory size1.1 MiB
0.0
73643 
1.0
 
13

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters220968
Distinct characters3
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
0.0 73643
> 99.9%
1.0 13
 
< 0.1%
(Missing) 2
 
< 0.1%

Length

2023-03-18T21:17:35.244678image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-03-18T21:17:35.336328image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
0.0 73643
> 99.9%
1.0 13
 
< 0.1%

Most occurring characters

ValueCountFrequency (%)
0 147299
66.7%
. 73656
33.3%
1 13
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 147312
66.7%
Other Punctuation 73656
33.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 147299
> 99.9%
1 13
 
< 0.1%
Other Punctuation
ValueCountFrequency (%)
. 73656
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 220968
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 147299
66.7%
. 73656
33.3%
1 13
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 220968
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 147299
66.7%
. 73656
33.3%
1 13
 
< 0.1%

Activity Type_Boating - Motorized Pleasure Craft
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing2
Missing (%)< 0.1%
Memory size1.1 MiB
0.0
73600 
1.0
 
56

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters220968
Distinct characters3
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
0.0 73600
99.9%
1.0 56
 
0.1%
(Missing) 2
 
< 0.1%

Length

2023-03-18T21:17:35.414356image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-03-18T21:17:35.506209image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
0.0 73600
99.9%
1.0 56
 
0.1%

Most occurring characters

ValueCountFrequency (%)
0 147256
66.6%
. 73656
33.3%
1 56
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 147312
66.7%
Other Punctuation 73656
33.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 147256
> 99.9%
1 56
 
< 0.1%
Other Punctuation
ValueCountFrequency (%)
. 73656
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 220968
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 147256
66.6%
. 73656
33.3%
1 56
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 220968
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 147256
66.6%
. 73656
33.3%
1 56
 
< 0.1%

Activity Type_Bush Party
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing2
Missing (%)< 0.1%
Memory size1.1 MiB
0.0
73654 
1.0
 
2

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters220968
Distinct characters3
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
0.0 73654
> 99.9%
1.0 2
 
< 0.1%
(Missing) 2
 
< 0.1%

Length

2023-03-18T21:17:35.583823image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-03-18T21:17:35.676414image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
0.0 73654
> 99.9%
1.0 2
 
< 0.1%

Most occurring characters

ValueCountFrequency (%)
0 147310
66.7%
. 73656
33.3%
1 2
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 147312
66.7%
Other Punctuation 73656
33.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 147310
> 99.9%
1 2
 
< 0.1%
Other Punctuation
ValueCountFrequency (%)
. 73656
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 220968
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 147310
66.7%
. 73656
33.3%
1 2
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 220968
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 147310
66.7%
. 73656
33.3%
1 2
 
< 0.1%
Distinct2
Distinct (%)< 0.1%
Missing2
Missing (%)< 0.1%
Memory size1.1 MiB
0.0
72897 
1.0
 
759

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters220968
Distinct characters3
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
0.0 72897
99.0%
1.0 759
 
1.0%
(Missing) 2
 
< 0.1%

Length

2023-03-18T21:17:35.756408image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-03-18T21:17:35.849278image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
0.0 72897
99.0%
1.0 759
 
1.0%

Most occurring characters

ValueCountFrequency (%)
0 146553
66.3%
. 73656
33.3%
1 759
 
0.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 147312
66.7%
Other Punctuation 73656
33.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 146553
99.5%
1 759
 
0.5%
Other Punctuation
ValueCountFrequency (%)
. 73656
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 220968
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 146553
66.3%
. 73656
33.3%
1 759
 
0.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 220968
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 146553
66.3%
. 73656
33.3%
1 759
 
0.3%
Distinct2
Distinct (%)< 0.1%
Missing2
Missing (%)< 0.1%
Memory size1.1 MiB
0.0
68036 
1.0
 
5620

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters220968
Distinct characters3
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
0.0 68036
92.4%
1.0 5620
 
7.6%
(Missing) 2
 
< 0.1%

Length

2023-03-18T21:17:35.926674image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-03-18T21:17:36.018321image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
0.0 68036
92.4%
1.0 5620
 
7.6%

Most occurring characters

ValueCountFrequency (%)
0 141692
64.1%
. 73656
33.3%
1 5620
 
2.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 147312
66.7%
Other Punctuation 73656
33.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 141692
96.2%
1 5620
 
3.8%
Other Punctuation
ValueCountFrequency (%)
. 73656
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 220968
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 141692
64.1%
. 73656
33.3%
1 5620
 
2.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 220968
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 141692
64.1%
. 73656
33.3%
1 5620
 
2.5%
Distinct2
Distinct (%)< 0.1%
Missing2
Missing (%)< 0.1%
Memory size1.1 MiB
0.0
73336 
1.0
 
320

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters220968
Distinct characters3
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
0.0 73336
99.6%
1.0 320
 
0.4%
(Missing) 2
 
< 0.1%

Length

2023-03-18T21:17:36.095666image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-03-18T21:17:36.187385image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
0.0 73336
99.6%
1.0 320
 
0.4%

Most occurring characters

ValueCountFrequency (%)
0 146992
66.5%
. 73656
33.3%
1 320
 
0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 147312
66.7%
Other Punctuation 73656
33.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 146992
99.8%
1 320
 
0.2%
Other Punctuation
ValueCountFrequency (%)
. 73656
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 220968
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 146992
66.5%
. 73656
33.3%
1 320
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 220968
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 146992
66.5%
. 73656
33.3%
1 320
 
0.1%
Distinct2
Distinct (%)< 0.1%
Missing2
Missing (%)< 0.1%
Memory size1.1 MiB
0.0
73640 
1.0
 
16

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters220968
Distinct characters3
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
0.0 73640
> 99.9%
1.0 16
 
< 0.1%
(Missing) 2
 
< 0.1%

Length

2023-03-18T21:17:36.264700image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-03-18T21:17:36.742554image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
0.0 73640
> 99.9%
1.0 16
 
< 0.1%

Most occurring characters

ValueCountFrequency (%)
0 147296
66.7%
. 73656
33.3%
1 16
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 147312
66.7%
Other Punctuation 73656
33.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 147296
> 99.9%
1 16
 
< 0.1%
Other Punctuation
ValueCountFrequency (%)
. 73656
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 220968
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 147296
66.7%
. 73656
33.3%
1 16
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 220968
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 147296
66.7%
. 73656
33.3%
1 16
 
< 0.1%
Distinct2
Distinct (%)< 0.1%
Missing2
Missing (%)< 0.1%
Memory size1.1 MiB
0.0
73613 
1.0
 
43

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters220968
Distinct characters3
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
0.0 73613
99.9%
1.0 43
 
0.1%
(Missing) 2
 
< 0.1%

Length

2023-03-18T21:17:36.819904image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-03-18T21:17:36.911831image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
0.0 73613
99.9%
1.0 43
 
0.1%

Most occurring characters

ValueCountFrequency (%)
0 147269
66.6%
. 73656
33.3%
1 43
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 147312
66.7%
Other Punctuation 73656
33.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 147269
> 99.9%
1 43
 
< 0.1%
Other Punctuation
ValueCountFrequency (%)
. 73656
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 220968
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 147269
66.6%
. 73656
33.3%
1 43
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 220968
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 147269
66.6%
. 73656
33.3%
1 43
 
< 0.1%
Distinct2
Distinct (%)< 0.1%
Missing2
Missing (%)< 0.1%
Memory size1.1 MiB
0.0
73641 
1.0
 
15

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters220968
Distinct characters3
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
0.0 73641
> 99.9%
1.0 15
 
< 0.1%
(Missing) 2
 
< 0.1%

Length

2023-03-18T21:17:36.990330image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-03-18T21:17:37.083368image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
0.0 73641
> 99.9%
1.0 15
 
< 0.1%

Most occurring characters

ValueCountFrequency (%)
0 147297
66.7%
. 73656
33.3%
1 15
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 147312
66.7%
Other Punctuation 73656
33.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 147297
> 99.9%
1 15
 
< 0.1%
Other Punctuation
ValueCountFrequency (%)
. 73656
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 220968
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 147297
66.7%
. 73656
33.3%
1 15
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 220968
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 147297
66.7%
. 73656
33.3%
1 15
 
< 0.1%

Activity Type_Canyoneering
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing2
Missing (%)< 0.1%
Memory size1.1 MiB
0.0
73654 
1.0
 
2

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters220968
Distinct characters3
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
0.0 73654
> 99.9%
1.0 2
 
< 0.1%
(Missing) 2
 
< 0.1%

Length

2023-03-18T21:17:37.162584image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-03-18T21:17:37.254273image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
0.0 73654
> 99.9%
1.0 2
 
< 0.1%

Most occurring characters

ValueCountFrequency (%)
0 147310
66.7%
. 73656
33.3%
1 2
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 147312
66.7%
Other Punctuation 73656
33.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 147310
> 99.9%
1 2
 
< 0.1%
Other Punctuation
ValueCountFrequency (%)
. 73656
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 220968
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 147310
66.7%
. 73656
33.3%
1 2
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 220968
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 147310
66.7%
. 73656
33.3%
1 2
 
< 0.1%

Activity Type_Climbing - Mountaineering
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing2
Missing (%)< 0.1%
Memory size1.1 MiB
0.0
73653 
1.0
 
3

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters220968
Distinct characters3
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
0.0 73653
> 99.9%
1.0 3
 
< 0.1%
(Missing) 2
 
< 0.1%

Length

2023-03-18T21:17:37.333288image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-03-18T21:17:37.426141image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
0.0 73653
> 99.9%
1.0 3
 
< 0.1%

Most occurring characters

ValueCountFrequency (%)
0 147309
66.7%
. 73656
33.3%
1 3
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 147312
66.7%
Other Punctuation 73656
33.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 147309
> 99.9%
1 3
 
< 0.1%
Other Punctuation
ValueCountFrequency (%)
. 73656
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 220968
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 147309
66.7%
. 73656
33.3%
1 3
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 220968
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 147309
66.7%
. 73656
33.3%
1 3
 
< 0.1%

Activity Type_Climbing - Technical Rock
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing2
Missing (%)< 0.1%
Memory size1.1 MiB
0.0
73650 
1.0
 
6

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters220968
Distinct characters3
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
0.0 73650
> 99.9%
1.0 6
 
< 0.1%
(Missing) 2
 
< 0.1%

Length

2023-03-18T21:17:37.506518image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-03-18T21:17:37.598545image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
0.0 73650
> 99.9%
1.0 6
 
< 0.1%

Most occurring characters

ValueCountFrequency (%)
0 147306
66.7%
. 73656
33.3%
1 6
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 147312
66.7%
Other Punctuation 73656
33.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 147306
> 99.9%
1 6
 
< 0.1%
Other Punctuation
ValueCountFrequency (%)
. 73656
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 220968
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 147306
66.7%
. 73656
33.3%
1 6
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 220968
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 147306
66.7%
. 73656
33.3%
1 6
 
< 0.1%

Activity Type_Climbing - Waterfall Ice
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing2
Missing (%)< 0.1%
Memory size1.1 MiB
0.0
73652 
1.0
 
4

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters220968
Distinct characters3
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
0.0 73652
> 99.9%
1.0 4
 
< 0.1%
(Missing) 2
 
< 0.1%

Length

2023-03-18T21:17:37.675941image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-03-18T21:17:37.767595image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
0.0 73652
> 99.9%
1.0 4
 
< 0.1%

Most occurring characters

ValueCountFrequency (%)
0 147308
66.7%
. 73656
33.3%
1 4
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 147312
66.7%
Other Punctuation 73656
33.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 147308
> 99.9%
1 4
 
< 0.1%
Other Punctuation
ValueCountFrequency (%)
. 73656
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 220968
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 147308
66.7%
. 73656
33.3%
1 4
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 220968
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 147308
66.7%
. 73656
33.3%
1 4
 
< 0.1%
Distinct2
Distinct (%)< 0.1%
Missing2
Missing (%)< 0.1%
Memory size1.1 MiB
0.0
73513 
1.0
 
143

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters220968
Distinct characters3
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
0.0 73513
99.8%
1.0 143
 
0.2%
(Missing) 2
 
< 0.1%

Length

2023-03-18T21:17:37.845166image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-03-18T21:17:37.938052image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
0.0 73513
99.8%
1.0 143
 
0.2%

Most occurring characters

ValueCountFrequency (%)
0 147169
66.6%
. 73656
33.3%
1 143
 
0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 147312
66.7%
Other Punctuation 73656
33.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 147169
99.9%
1 143
 
0.1%
Other Punctuation
ValueCountFrequency (%)
. 73656
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 220968
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 147169
66.6%
. 73656
33.3%
1 143
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 220968
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 147169
66.6%
. 73656
33.3%
1 143
 
0.1%
Distinct2
Distinct (%)< 0.1%
Missing2
Missing (%)< 0.1%
Memory size1.1 MiB
0.0
73537 
1.0
 
119

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters220968
Distinct characters3
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
0.0 73537
99.8%
1.0 119
 
0.2%
(Missing) 2
 
< 0.1%

Length

2023-03-18T21:17:38.015383image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-03-18T21:17:38.107104image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
0.0 73537
99.8%
1.0 119
 
0.2%

Most occurring characters

ValueCountFrequency (%)
0 147193
66.6%
. 73656
33.3%
1 119
 
0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 147312
66.7%
Other Punctuation 73656
33.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 147193
99.9%
1 119
 
0.1%
Other Punctuation
ValueCountFrequency (%)
. 73656
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 220968
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 147193
66.6%
. 73656
33.3%
1 119
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 220968
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 147193
66.6%
. 73656
33.3%
1 119
 
0.1%
Distinct2
Distinct (%)< 0.1%
Missing2
Missing (%)< 0.1%
Memory size1.1 MiB
0.0
73457 
1.0
 
199

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters220968
Distinct characters3
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
0.0 73457
99.7%
1.0 199
 
0.3%
(Missing) 2
 
< 0.1%

Length

2023-03-18T21:17:38.184308image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-03-18T21:17:38.277686image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
0.0 73457
99.7%
1.0 199
 
0.3%

Most occurring characters

ValueCountFrequency (%)
0 147113
66.6%
. 73656
33.3%
1 199
 
0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 147312
66.7%
Other Punctuation 73656
33.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 147113
99.9%
1 199
 
0.1%
Other Punctuation
ValueCountFrequency (%)
. 73656
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 220968
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 147113
66.6%
. 73656
33.3%
1 199
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 220968
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 147113
66.6%
. 73656
33.3%
1 199
 
0.1%
Distinct2
Distinct (%)< 0.1%
Missing2
Missing (%)< 0.1%
Memory size1.1 MiB
0.0
73323 
1.0
 
333

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters220968
Distinct characters3
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
0.0 73323
99.5%
1.0 333
 
0.5%
(Missing) 2
 
< 0.1%

Length

2023-03-18T21:17:38.354899image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-03-18T21:17:38.446540image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
0.0 73323
99.5%
1.0 333
 
0.5%

Most occurring characters

ValueCountFrequency (%)
0 146979
66.5%
. 73656
33.3%
1 333
 
0.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 147312
66.7%
Other Punctuation 73656
33.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 146979
99.8%
1 333
 
0.2%
Other Punctuation
ValueCountFrequency (%)
. 73656
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 220968
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 146979
66.5%
. 73656
33.3%
1 333
 
0.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 220968
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 146979
66.5%
. 73656
33.3%
1 333
 
0.2%

Activity Type_Cycling - Winter
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing2
Missing (%)< 0.1%
Memory size1.1 MiB
0.0
73653 
1.0
 
3

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters220968
Distinct characters3
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
0.0 73653
> 99.9%
1.0 3
 
< 0.1%
(Missing) 2
 
< 0.1%

Length

2023-03-18T21:17:38.524323image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-03-18T21:17:38.617544image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
0.0 73653
> 99.9%
1.0 3
 
< 0.1%

Most occurring characters

ValueCountFrequency (%)
0 147309
66.7%
. 73656
33.3%
1 3
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 147312
66.7%
Other Punctuation 73656
33.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 147309
> 99.9%
1 3
 
< 0.1%
Other Punctuation
ValueCountFrequency (%)
. 73656
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 220968
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 147309
66.7%
. 73656
33.3%
1 3
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 220968
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 147309
66.7%
. 73656
33.3%
1 3
 
< 0.1%

Activity Type_Dog Walking
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing2
Missing (%)< 0.1%
Memory size1.1 MiB
0.0
73060 
1.0
 
596

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters220968
Distinct characters3
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
0.0 73060
99.2%
1.0 596
 
0.8%
(Missing) 2
 
< 0.1%

Length

2023-03-18T21:17:38.695184image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-03-18T21:17:38.786822image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
0.0 73060
99.2%
1.0 596
 
0.8%

Most occurring characters

ValueCountFrequency (%)
0 146716
66.4%
. 73656
33.3%
1 596
 
0.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 147312
66.7%
Other Punctuation 73656
33.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 146716
99.6%
1 596
 
0.4%
Other Punctuation
ValueCountFrequency (%)
. 73656
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 220968
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 146716
66.4%
. 73656
33.3%
1 596
 
0.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 220968
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 146716
66.4%
. 73656
33.3%
1 596
 
0.3%

Activity Type_Dogsledding
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing2
Missing (%)< 0.1%
Memory size1.1 MiB
0.0
73654 
1.0
 
2

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters220968
Distinct characters3
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
0.0 73654
> 99.9%
1.0 2
 
< 0.1%
(Missing) 2
 
< 0.1%

Length

2023-03-18T21:17:38.864198image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-03-18T21:17:38.955931image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
0.0 73654
> 99.9%
1.0 2
 
< 0.1%

Most occurring characters

ValueCountFrequency (%)
0 147310
66.7%
. 73656
33.3%
1 2
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 147312
66.7%
Other Punctuation 73656
33.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 147310
> 99.9%
1 2
 
< 0.1%
Other Punctuation
ValueCountFrequency (%)
. 73656
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 220968
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 147310
66.7%
. 73656
33.3%
1 2
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 220968
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 147310
66.7%
. 73656
33.3%
1 2
 
< 0.1%
Distinct2
Distinct (%)< 0.1%
Missing2
Missing (%)< 0.1%
Memory size1.1 MiB
0.0
73163 
1.0
 
493

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters220968
Distinct characters3
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
0.0 73163
99.3%
1.0 493
 
0.7%
(Missing) 2
 
< 0.1%

Length

2023-03-18T21:17:39.034616image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-03-18T21:17:39.127911image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
0.0 73163
99.3%
1.0 493
 
0.7%

Most occurring characters

ValueCountFrequency (%)
0 146819
66.4%
. 73656
33.3%
1 493
 
0.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 147312
66.7%
Other Punctuation 73656
33.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 146819
99.7%
1 493
 
0.3%
Other Punctuation
ValueCountFrequency (%)
. 73656
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 220968
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 146819
66.4%
. 73656
33.3%
1 493
 
0.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 220968
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 146819
66.4%
. 73656
33.3%
1 493
 
0.2%
Distinct2
Distinct (%)< 0.1%
Missing2
Missing (%)< 0.1%
Memory size1.1 MiB
0.0
48249 
1.0
25407 

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters220968
Distinct characters3
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row1.0
5th row1.0

Common Values

ValueCountFrequency (%)
0.0 48249
65.5%
1.0 25407
34.5%
(Missing) 2
 
< 0.1%

Length

2023-03-18T21:17:39.206445image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-03-18T21:17:39.298665image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
0.0 48249
65.5%
1.0 25407
34.5%

Most occurring characters

ValueCountFrequency (%)
0 121905
55.2%
. 73656
33.3%
1 25407
 
11.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 147312
66.7%
Other Punctuation 73656
33.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 121905
82.8%
1 25407
 
17.2%
Other Punctuation
ValueCountFrequency (%)
. 73656
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 220968
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 121905
55.2%
. 73656
33.3%
1 25407
 
11.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 220968
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 121905
55.2%
. 73656
33.3%
1 25407
 
11.5%
Distinct2
Distinct (%)< 0.1%
Missing2
Missing (%)< 0.1%
Memory size1.1 MiB
0.0
73544 
1.0
 
112

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters220968
Distinct characters3
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
0.0 73544
99.8%
1.0 112
 
0.2%
(Missing) 2
 
< 0.1%

Length

2023-03-18T21:17:39.378819image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-03-18T21:17:39.590627image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
0.0 73544
99.8%
1.0 112
 
0.2%

Most occurring characters

ValueCountFrequency (%)
0 147200
66.6%
. 73656
33.3%
1 112
 
0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 147312
66.7%
Other Punctuation 73656
33.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 147200
99.9%
1 112
 
0.1%
Other Punctuation
ValueCountFrequency (%)
. 73656
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 220968
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 147200
66.6%
. 73656
33.3%
1 112
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 220968
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 147200
66.6%
. 73656
33.3%
1 112
 
0.1%
Distinct2
Distinct (%)< 0.1%
Missing2
Missing (%)< 0.1%
Memory size1.1 MiB
0.0
73607 
1.0
 
49

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters220968
Distinct characters3
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
0.0 73607
99.9%
1.0 49
 
0.1%
(Missing) 2
 
< 0.1%

Length

2023-03-18T21:17:39.668112image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-03-18T21:17:39.761141image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
0.0 73607
99.9%
1.0 49
 
0.1%

Most occurring characters

ValueCountFrequency (%)
0 147263
66.6%
. 73656
33.3%
1 49
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 147312
66.7%
Other Punctuation 73656
33.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 147263
> 99.9%
1 49
 
< 0.1%
Other Punctuation
ValueCountFrequency (%)
. 73656
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 220968
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 147263
66.6%
. 73656
33.3%
1 49
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 220968
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 147263
66.6%
. 73656
33.3%
1 49
 
< 0.1%

Activity Type_Flight - HETS
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing2
Missing (%)< 0.1%
Memory size1.1 MiB
0.0
73655 
1.0
 
1

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters220968
Distinct characters3
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
0.0 73655
> 99.9%
1.0 1
 
< 0.1%
(Missing) 2
 
< 0.1%

Length

2023-03-18T21:17:39.840060image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-03-18T21:17:39.932991image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
0.0 73655
> 99.9%
1.0 1
 
< 0.1%

Most occurring characters

ValueCountFrequency (%)
0 147311
66.7%
. 73656
33.3%
1 1
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 147312
66.7%
Other Punctuation 73656
33.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 147311
> 99.9%
1 1
 
< 0.1%
Other Punctuation
ValueCountFrequency (%)
. 73656
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 220968
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 147311
66.7%
. 73656
33.3%
1 1
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 220968
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 147311
66.7%
. 73656
33.3%
1 1
 
< 0.1%

Activity Type_Flight - Hang-gliding/Parapenting
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing2
Missing (%)< 0.1%
Memory size1.1 MiB
0.0
73653 
1.0
 
3

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters220968
Distinct characters3
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
0.0 73653
> 99.9%
1.0 3
 
< 0.1%
(Missing) 2
 
< 0.1%

Length

2023-03-18T21:17:40.010874image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-03-18T21:17:40.102445image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
0.0 73653
> 99.9%
1.0 3
 
< 0.1%

Most occurring characters

ValueCountFrequency (%)
0 147309
66.7%
. 73656
33.3%
1 3
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 147312
66.7%
Other Punctuation 73656
33.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 147309
> 99.9%
1 3
 
< 0.1%
Other Punctuation
ValueCountFrequency (%)
. 73656
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 220968
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 147309
66.7%
. 73656
33.3%
1 3
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 220968
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 147309
66.7%
. 73656
33.3%
1 3
 
< 0.1%
Distinct2
Distinct (%)< 0.1%
Missing2
Missing (%)< 0.1%
Memory size1.1 MiB
0.0
73651 
1.0
 
5

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters220968
Distinct characters3
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
0.0 73651
> 99.9%
1.0 5
 
< 0.1%
(Missing) 2
 
< 0.1%

Length

2023-03-18T21:17:40.179863image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-03-18T21:17:40.271723image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
0.0 73651
> 99.9%
1.0 5
 
< 0.1%

Most occurring characters

ValueCountFrequency (%)
0 147307
66.7%
. 73656
33.3%
1 5
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 147312
66.7%
Other Punctuation 73656
33.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 147307
> 99.9%
1 5
 
< 0.1%
Other Punctuation
ValueCountFrequency (%)
. 73656
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 220968
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 147307
66.7%
. 73656
33.3%
1 5
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 220968
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 147307
66.7%
. 73656
33.3%
1 5
 
< 0.1%
Distinct2
Distinct (%)< 0.1%
Missing2
Missing (%)< 0.1%
Memory size1.1 MiB
0.0
73652 
1.0
 
4

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters220968
Distinct characters3
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
0.0 73652
> 99.9%
1.0 4
 
< 0.1%
(Missing) 2
 
< 0.1%

Length

2023-03-18T21:17:40.349168image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-03-18T21:17:40.440751image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
0.0 73652
> 99.9%
1.0 4
 
< 0.1%

Most occurring characters

ValueCountFrequency (%)
0 147308
66.7%
. 73656
33.3%
1 4
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 147312
66.7%
Other Punctuation 73656
33.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 147308
> 99.9%
1 4
 
< 0.1%
Other Punctuation
ValueCountFrequency (%)
. 73656
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 220968
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 147308
66.7%
. 73656
33.3%
1 4
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 220968
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 147308
66.7%
. 73656
33.3%
1 4
 
< 0.1%
Distinct2
Distinct (%)< 0.1%
Missing2
Missing (%)< 0.1%
Memory size1.1 MiB
0.0
72058 
1.0
 
1598

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters220968
Distinct characters3
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
0.0 72058
97.8%
1.0 1598
 
2.2%
(Missing) 2
 
< 0.1%

Length

2023-03-18T21:17:40.518617image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-03-18T21:17:40.610453image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
0.0 72058
97.8%
1.0 1598
 
2.2%

Most occurring characters

ValueCountFrequency (%)
0 145714
65.9%
. 73656
33.3%
1 1598
 
0.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 147312
66.7%
Other Punctuation 73656
33.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 145714
98.9%
1 1598
 
1.1%
Other Punctuation
ValueCountFrequency (%)
. 73656
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 220968
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 145714
65.9%
. 73656
33.3%
1 1598
 
0.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 220968
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 145714
65.9%
. 73656
33.3%
1 1598
 
0.7%
Distinct2
Distinct (%)< 0.1%
Missing2
Missing (%)< 0.1%
Memory size1.1 MiB
0.0
73626 
1.0
 
30

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters220968
Distinct characters3
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
0.0 73626
> 99.9%
1.0 30
 
< 0.1%
(Missing) 2
 
< 0.1%

Length

2023-03-18T21:17:40.688078image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-03-18T21:17:40.779730image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
0.0 73626
> 99.9%
1.0 30
 
< 0.1%

Most occurring characters

ValueCountFrequency (%)
0 147282
66.7%
. 73656
33.3%
1 30
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 147312
66.7%
Other Punctuation 73656
33.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 147282
> 99.9%
1 30
 
< 0.1%
Other Punctuation
ValueCountFrequency (%)
. 73656
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 220968
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 147282
66.7%
. 73656
33.3%
1 30
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 220968
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 147282
66.7%
. 73656
33.3%
1 30
 
< 0.1%
Distinct2
Distinct (%)< 0.1%
Missing2
Missing (%)< 0.1%
Memory size1.1 MiB
0.0
73572 
1.0
 
84

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters220968
Distinct characters3
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
0.0 73572
99.9%
1.0 84
 
0.1%
(Missing) 2
 
< 0.1%

Length

2023-03-18T21:17:40.856684image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-03-18T21:17:40.948268image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
0.0 73572
99.9%
1.0 84
 
0.1%

Most occurring characters

ValueCountFrequency (%)
0 147228
66.6%
. 73656
33.3%
1 84
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 147312
66.7%
Other Punctuation 73656
33.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 147228
99.9%
1 84
 
0.1%
Other Punctuation
ValueCountFrequency (%)
. 73656
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 220968
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 147228
66.6%
. 73656
33.3%
1 84
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 220968
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 147228
66.6%
. 73656
33.3%
1 84
 
< 0.1%
Distinct2
Distinct (%)< 0.1%
Missing2
Missing (%)< 0.1%
Memory size1.1 MiB
0.0
73491 
1.0
 
165

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters220968
Distinct characters3
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
0.0 73491
99.8%
1.0 165
 
0.2%
(Missing) 2
 
< 0.1%

Length

2023-03-18T21:17:41.027060image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-03-18T21:17:41.119955image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
0.0 73491
99.8%
1.0 165
 
0.2%

Most occurring characters

ValueCountFrequency (%)
0 147147
66.6%
. 73656
33.3%
1 165
 
0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 147312
66.7%
Other Punctuation 73656
33.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 147147
99.9%
1 165
 
0.1%
Other Punctuation
ValueCountFrequency (%)
. 73656
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 220968
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 147147
66.6%
. 73656
33.3%
1 165
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 220968
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 147147
66.6%
. 73656
33.3%
1 165
 
0.1%
Distinct2
Distinct (%)< 0.1%
Missing2
Missing (%)< 0.1%
Memory size1.1 MiB
0.0
73240 
1.0
 
416

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters220968
Distinct characters3
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
0.0 73240
99.4%
1.0 416
 
0.6%
(Missing) 2
 
< 0.1%

Length

2023-03-18T21:17:41.197159image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-03-18T21:17:41.288493image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
0.0 73240
99.4%
1.0 416
 
0.6%

Most occurring characters

ValueCountFrequency (%)
0 146896
66.5%
. 73656
33.3%
1 416
 
0.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 147312
66.7%
Other Punctuation 73656
33.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 146896
99.7%
1 416
 
0.3%
Other Punctuation
ValueCountFrequency (%)
. 73656
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 220968
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 146896
66.5%
. 73656
33.3%
1 416
 
0.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 220968
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 146896
66.5%
. 73656
33.3%
1 416
 
0.2%
Distinct2
Distinct (%)< 0.1%
Missing2
Missing (%)< 0.1%
Memory size1.1 MiB
0.0
72933 
1.0
 
723

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters220968
Distinct characters3
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
0.0 72933
99.0%
1.0 723
 
1.0%
(Missing) 2
 
< 0.1%

Length

2023-03-18T21:17:41.365584image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-03-18T21:17:41.456813image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
0.0 72933
99.0%
1.0 723
 
1.0%

Most occurring characters

ValueCountFrequency (%)
0 146589
66.3%
. 73656
33.3%
1 723
 
0.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 147312
66.7%
Other Punctuation 73656
33.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 146589
99.5%
1 723
 
0.5%
Other Punctuation
ValueCountFrequency (%)
. 73656
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 220968
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 146589
66.3%
. 73656
33.3%
1 723
 
0.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 220968
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 146589
66.3%
. 73656
33.3%
1 723
 
0.3%
Distinct2
Distinct (%)< 0.1%
Missing2
Missing (%)< 0.1%
Memory size1.1 MiB
0.0
67966 
1.0
 
5690

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters220968
Distinct characters3
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
0.0 67966
92.3%
1.0 5690
 
7.7%
(Missing) 2
 
< 0.1%

Length

2023-03-18T21:17:41.537305image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-03-18T21:17:41.629809image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
0.0 67966
92.3%
1.0 5690
 
7.7%

Most occurring characters

ValueCountFrequency (%)
0 141622
64.1%
. 73656
33.3%
1 5690
 
2.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 147312
66.7%
Other Punctuation 73656
33.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 141622
96.1%
1 5690
 
3.9%
Other Punctuation
ValueCountFrequency (%)
. 73656
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 220968
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 141622
64.1%
. 73656
33.3%
1 5690
 
2.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 220968
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 141622
64.1%
. 73656
33.3%
1 5690
 
2.6%
Distinct2
Distinct (%)< 0.1%
Missing2
Missing (%)< 0.1%
Memory size1.1 MiB
0.0
73519 
1.0
 
137

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters220968
Distinct characters3
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
0.0 73519
99.8%
1.0 137
 
0.2%
(Missing) 2
 
< 0.1%

Length

2023-03-18T21:17:41.707808image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-03-18T21:17:41.799215image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
0.0 73519
99.8%
1.0 137
 
0.2%

Most occurring characters

ValueCountFrequency (%)
0 147175
66.6%
. 73656
33.3%
1 137
 
0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 147312
66.7%
Other Punctuation 73656
33.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 147175
99.9%
1 137
 
0.1%
Other Punctuation
ValueCountFrequency (%)
. 73656
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 220968
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 147175
66.6%
. 73656
33.3%
1 137
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 220968
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 147175
66.6%
. 73656
33.3%
1 137
 
0.1%
Distinct2
Distinct (%)< 0.1%
Missing2
Missing (%)< 0.1%
Memory size1.1 MiB
0.0
73642 
1.0
 
14

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters220968
Distinct characters3
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
0.0 73642
> 99.9%
1.0 14
 
< 0.1%
(Missing) 2
 
< 0.1%

Length

2023-03-18T21:17:41.877671image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-03-18T21:17:41.972236image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
0.0 73642
> 99.9%
1.0 14
 
< 0.1%

Most occurring characters

ValueCountFrequency (%)
0 147298
66.7%
. 73656
33.3%
1 14
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 147312
66.7%
Other Punctuation 73656
33.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 147298
> 99.9%
1 14
 
< 0.1%
Other Punctuation
ValueCountFrequency (%)
. 73656
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 220968
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 147298
66.7%
. 73656
33.3%
1 14
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 220968
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 147298
66.7%
. 73656
33.3%
1 14
 
< 0.1%
Distinct2
Distinct (%)< 0.1%
Missing2
Missing (%)< 0.1%
Memory size1.1 MiB
0.0
73652 
1.0
 
4

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters220968
Distinct characters3
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
0.0 73652
> 99.9%
1.0 4
 
< 0.1%
(Missing) 2
 
< 0.1%

Length

2023-03-18T21:17:42.055293image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-03-18T21:17:42.154451image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
0.0 73652
> 99.9%
1.0 4
 
< 0.1%

Most occurring characters

ValueCountFrequency (%)
0 147308
66.7%
. 73656
33.3%
1 4
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 147312
66.7%
Other Punctuation 73656
33.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 147308
> 99.9%
1 4
 
< 0.1%
Other Punctuation
ValueCountFrequency (%)
. 73656
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 220968
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 147308
66.7%
. 73656
33.3%
1 4
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 220968
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 147308
66.7%
. 73656
33.3%
1 4
 
< 0.1%
Distinct2
Distinct (%)< 0.1%
Missing2
Missing (%)< 0.1%
Memory size1.1 MiB
0.0
73644 
1.0
 
12

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters220968
Distinct characters3
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
0.0 73644
> 99.9%
1.0 12
 
< 0.1%
(Missing) 2
 
< 0.1%

Length

2023-03-18T21:17:42.237371image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-03-18T21:17:42.459148image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
0.0 73644
> 99.9%
1.0 12
 
< 0.1%

Most occurring characters

ValueCountFrequency (%)
0 147300
66.7%
. 73656
33.3%
1 12
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 147312
66.7%
Other Punctuation 73656
33.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 147300
> 99.9%
1 12
 
< 0.1%
Other Punctuation
ValueCountFrequency (%)
. 73656
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 220968
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 147300
66.7%
. 73656
33.3%
1 12
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 220968
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 147300
66.7%
. 73656
33.3%
1 12
 
< 0.1%
Distinct2
Distinct (%)< 0.1%
Missing2
Missing (%)< 0.1%
Memory size1.1 MiB
0.0
73640 
1.0
 
16

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters220968
Distinct characters3
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
0.0 73640
> 99.9%
1.0 16
 
< 0.1%
(Missing) 2
 
< 0.1%

Length

2023-03-18T21:17:42.543750image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-03-18T21:17:42.638548image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
0.0 73640
> 99.9%
1.0 16
 
< 0.1%

Most occurring characters

ValueCountFrequency (%)
0 147296
66.7%
. 73656
33.3%
1 16
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 147312
66.7%
Other Punctuation 73656
33.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 147296
> 99.9%
1 16
 
< 0.1%
Other Punctuation
ValueCountFrequency (%)
. 73656
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 220968
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 147296
66.7%
. 73656
33.3%
1 16
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 220968
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 147296
66.7%
. 73656
33.3%
1 16
 
< 0.1%

Activity Type_Kayaking - Swiftwater
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing2
Missing (%)< 0.1%
Memory size1.1 MiB
0.0
73654 
1.0
 
2

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters220968
Distinct characters3
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
0.0 73654
> 99.9%
1.0 2
 
< 0.1%
(Missing) 2
 
< 0.1%

Length

2023-03-18T21:17:42.716695image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-03-18T21:17:42.808172image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
0.0 73654
> 99.9%
1.0 2
 
< 0.1%

Most occurring characters

ValueCountFrequency (%)
0 147310
66.7%
. 73656
33.3%
1 2
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 147312
66.7%
Other Punctuation 73656
33.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 147310
> 99.9%
1 2
 
< 0.1%
Other Punctuation
ValueCountFrequency (%)
. 73656
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 220968
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 147310
66.7%
. 73656
33.3%
1 2
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 220968
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 147310
66.7%
. 73656
33.3%
1 2
 
< 0.1%
Distinct2
Distinct (%)< 0.1%
Missing2
Missing (%)< 0.1%
Memory size1.1 MiB
0.0
73655 
1.0
 
1

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters220968
Distinct characters3
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
0.0 73655
> 99.9%
1.0 1
 
< 0.1%
(Missing) 2
 
< 0.1%

Length

2023-03-18T21:17:42.890524image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-03-18T21:17:42.984628image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
0.0 73655
> 99.9%
1.0 1
 
< 0.1%

Most occurring characters

ValueCountFrequency (%)
0 147311
66.7%
. 73656
33.3%
1 1
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 147312
66.7%
Other Punctuation 73656
33.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 147311
> 99.9%
1 1
 
< 0.1%
Other Punctuation
ValueCountFrequency (%)
. 73656
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 220968
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 147311
66.7%
. 73656
33.3%
1 1
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 220968
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 147311
66.7%
. 73656
33.3%
1 1
 
< 0.1%

Activity Type_Not Applicable
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing2
Missing (%)< 0.1%
Memory size1.1 MiB
0.0
73651 
1.0
 
5

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters220968
Distinct characters3
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
0.0 73651
> 99.9%
1.0 5
 
< 0.1%
(Missing) 2
 
< 0.1%

Length

2023-03-18T21:17:43.062658image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-03-18T21:17:43.159092image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
0.0 73651
> 99.9%
1.0 5
 
< 0.1%

Most occurring characters

ValueCountFrequency (%)
0 147307
66.7%
. 73656
33.3%
1 5
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 147312
66.7%
Other Punctuation 73656
33.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 147307
> 99.9%
1 5
 
< 0.1%
Other Punctuation
ValueCountFrequency (%)
. 73656
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 220968
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 147307
66.7%
. 73656
33.3%
1 5
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 220968
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 147307
66.7%
. 73656
33.3%
1 5
 
< 0.1%

Activity Type_Orienteering / Geocaching
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing2
Missing (%)< 0.1%
Memory size1.1 MiB
0.0
73655 
1.0
 
1

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters220968
Distinct characters3
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
0.0 73655
> 99.9%
1.0 1
 
< 0.1%
(Missing) 2
 
< 0.1%

Length

2023-03-18T21:17:43.238424image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-03-18T21:17:43.331112image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
0.0 73655
> 99.9%
1.0 1
 
< 0.1%

Most occurring characters

ValueCountFrequency (%)
0 147311
66.7%
. 73656
33.3%
1 1
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 147312
66.7%
Other Punctuation 73656
33.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 147311
> 99.9%
1 1
 
< 0.1%
Other Punctuation
ValueCountFrequency (%)
. 73656
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 220968
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 147311
66.7%
. 73656
33.3%
1 1
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 220968
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 147311
66.7%
. 73656
33.3%
1 1
 
< 0.1%
Distinct2
Distinct (%)< 0.1%
Missing2
Missing (%)< 0.1%
Memory size1.1 MiB
0.0
73231 
1.0
 
425

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters220968
Distinct characters3
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
0.0 73231
99.4%
1.0 425
 
0.6%
(Missing) 2
 
< 0.1%

Length

2023-03-18T21:17:43.409717image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-03-18T21:17:43.502591image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
0.0 73231
99.4%
1.0 425
 
0.6%

Most occurring characters

ValueCountFrequency (%)
0 146887
66.5%
. 73656
33.3%
1 425
 
0.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 147312
66.7%
Other Punctuation 73656
33.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 146887
99.7%
1 425
 
0.3%
Other Punctuation
ValueCountFrequency (%)
. 73656
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 220968
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 146887
66.5%
. 73656
33.3%
1 425
 
0.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 220968
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 146887
66.5%
. 73656
33.3%
1 425
 
0.2%

Activity Type_Paddleboarding - Coastal
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing2
Missing (%)< 0.1%
Memory size1.1 MiB
0.0
73655 
1.0
 
1

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters220968
Distinct characters3
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
0.0 73655
> 99.9%
1.0 1
 
< 0.1%
(Missing) 2
 
< 0.1%

Length

2023-03-18T21:17:43.581801image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-03-18T21:17:43.675315image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
0.0 73655
> 99.9%
1.0 1
 
< 0.1%

Most occurring characters

ValueCountFrequency (%)
0 147311
66.7%
. 73656
33.3%
1 1
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 147312
66.7%
Other Punctuation 73656
33.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 147311
> 99.9%
1 1
 
< 0.1%
Other Punctuation
ValueCountFrequency (%)
. 73656
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 220968
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 147311
66.7%
. 73656
33.3%
1 1
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 220968
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 147311
66.7%
. 73656
33.3%
1 1
 
< 0.1%
Distinct2
Distinct (%)< 0.1%
Missing2
Missing (%)< 0.1%
Memory size1.1 MiB
0.0
73643 
1.0
 
13

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters220968
Distinct characters3
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
0.0 73643
> 99.9%
1.0 13
 
< 0.1%
(Missing) 2
 
< 0.1%

Length

2023-03-18T21:17:43.754326image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-03-18T21:17:43.847615image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
0.0 73643
> 99.9%
1.0 13
 
< 0.1%

Most occurring characters

ValueCountFrequency (%)
0 147299
66.7%
. 73656
33.3%
1 13
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 147312
66.7%
Other Punctuation 73656
33.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 147299
> 99.9%
1 13
 
< 0.1%
Other Punctuation
ValueCountFrequency (%)
. 73656
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 220968
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 147299
66.7%
. 73656
33.3%
1 13
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 220968
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 147299
66.7%
. 73656
33.3%
1 13
 
< 0.1%
Distinct2
Distinct (%)< 0.1%
Missing2
Missing (%)< 0.1%
Memory size1.1 MiB
0.0
69460 
1.0
 
4196

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters220968
Distinct characters3
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
0.0 69460
94.3%
1.0 4196
 
5.7%
(Missing) 2
 
< 0.1%

Length

2023-03-18T21:17:43.925815image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-03-18T21:17:44.018217image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
0.0 69460
94.3%
1.0 4196
 
5.7%

Most occurring characters

ValueCountFrequency (%)
0 143116
64.8%
. 73656
33.3%
1 4196
 
1.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 147312
66.7%
Other Punctuation 73656
33.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 143116
97.2%
1 4196
 
2.8%
Other Punctuation
ValueCountFrequency (%)
. 73656
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 220968
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 143116
64.8%
. 73656
33.3%
1 4196
 
1.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 220968
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 143116
64.8%
. 73656
33.3%
1 4196
 
1.9%

Activity Type_Park Ops - Avalanche Forecasting
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing2
Missing (%)< 0.1%
Memory size1.1 MiB
0.0
73651 
1.0
 
5

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters220968
Distinct characters3
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
0.0 73651
> 99.9%
1.0 5
 
< 0.1%
(Missing) 2
 
< 0.1%

Length

2023-03-18T21:17:44.097122image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-03-18T21:17:44.189104image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
0.0 73651
> 99.9%
1.0 5
 
< 0.1%

Most occurring characters

ValueCountFrequency (%)
0 147307
66.7%
. 73656
33.3%
1 5
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 147312
66.7%
Other Punctuation 73656
33.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 147307
> 99.9%
1 5
 
< 0.1%
Other Punctuation
ValueCountFrequency (%)
. 73656
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 220968
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 147307
66.7%
. 73656
33.3%
1 5
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 220968
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 147307
66.7%
. 73656
33.3%
1 5
 
< 0.1%
Distinct2
Distinct (%)< 0.1%
Missing2
Missing (%)< 0.1%
Memory size1.1 MiB
0.0
73651 
1.0
 
5

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters220968
Distinct characters3
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
0.0 73651
> 99.9%
1.0 5
 
< 0.1%
(Missing) 2
 
< 0.1%

Length

2023-03-18T21:17:44.267486image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-03-18T21:17:44.359017image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
0.0 73651
> 99.9%
1.0 5
 
< 0.1%

Most occurring characters

ValueCountFrequency (%)
0 147307
66.7%
. 73656
33.3%
1 5
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 147312
66.7%
Other Punctuation 73656
33.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 147307
> 99.9%
1 5
 
< 0.1%
Other Punctuation
ValueCountFrequency (%)
. 73656
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 220968
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 147307
66.7%
. 73656
33.3%
1 5
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 220968
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 147307
66.7%
. 73656
33.3%
1 5
 
< 0.1%
Distinct2
Distinct (%)< 0.1%
Missing2
Missing (%)< 0.1%
Memory size1.1 MiB
0.0
73654 
1.0
 
2

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters220968
Distinct characters3
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
0.0 73654
> 99.9%
1.0 2
 
< 0.1%
(Missing) 2
 
< 0.1%

Length

2023-03-18T21:17:44.436412image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-03-18T21:17:44.527912image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
0.0 73654
> 99.9%
1.0 2
 
< 0.1%

Most occurring characters

ValueCountFrequency (%)
0 147310
66.7%
. 73656
33.3%
1 2
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 147312
66.7%
Other Punctuation 73656
33.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 147310
> 99.9%
1 2
 
< 0.1%
Other Punctuation
ValueCountFrequency (%)
. 73656
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 220968
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 147310
66.7%
. 73656
33.3%
1 2
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 220968
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 147310
66.7%
. 73656
33.3%
1 2
 
< 0.1%
Distinct2
Distinct (%)< 0.1%
Missing2
Missing (%)< 0.1%
Memory size1.1 MiB
0.0
73651 
1.0
 
5

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters220968
Distinct characters3
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
0.0 73651
> 99.9%
1.0 5
 
< 0.1%
(Missing) 2
 
< 0.1%

Length

2023-03-18T21:17:44.605394image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-03-18T21:17:44.696773image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
0.0 73651
> 99.9%
1.0 5
 
< 0.1%

Most occurring characters

ValueCountFrequency (%)
0 147307
66.7%
. 73656
33.3%
1 5
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 147312
66.7%
Other Punctuation 73656
33.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 147307
> 99.9%
1 5
 
< 0.1%
Other Punctuation
ValueCountFrequency (%)
. 73656
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 220968
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 147307
66.7%
. 73656
33.3%
1 5
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 220968
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 147307
66.7%
. 73656
33.3%
1 5
 
< 0.1%
Distinct2
Distinct (%)< 0.1%
Missing2
Missing (%)< 0.1%
Memory size1.1 MiB
0.0
73083 
1.0
 
573

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters220968
Distinct characters3
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
0.0 73083
99.2%
1.0 573
 
0.8%
(Missing) 2
 
< 0.1%

Length

2023-03-18T21:17:44.774362image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-03-18T21:17:44.865676image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
0.0 73083
99.2%
1.0 573
 
0.8%

Most occurring characters

ValueCountFrequency (%)
0 146739
66.4%
. 73656
33.3%
1 573
 
0.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 147312
66.7%
Other Punctuation 73656
33.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 146739
99.6%
1 573
 
0.4%
Other Punctuation
ValueCountFrequency (%)
. 73656
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 220968
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 146739
66.4%
. 73656
33.3%
1 573
 
0.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 220968
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 146739
66.4%
. 73656
33.3%
1 573
 
0.3%
Distinct2
Distinct (%)< 0.1%
Missing2
Missing (%)< 0.1%
Memory size1.1 MiB
0.0
73627 
1.0
 
29

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters220968
Distinct characters3
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
0.0 73627
> 99.9%
1.0 29
 
< 0.1%
(Missing) 2
 
< 0.1%

Length

2023-03-18T21:17:44.947721image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-03-18T21:17:45.040305image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
0.0 73627
> 99.9%
1.0 29
 
< 0.1%

Most occurring characters

ValueCountFrequency (%)
0 147283
66.7%
. 73656
33.3%
1 29
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 147312
66.7%
Other Punctuation 73656
33.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 147283
> 99.9%
1 29
 
< 0.1%
Other Punctuation
ValueCountFrequency (%)
. 73656
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 220968
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 147283
66.7%
. 73656
33.3%
1 29
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 220968
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 147283
66.7%
. 73656
33.3%
1 29
 
< 0.1%

Activity Type_Rafting - Flatwater
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing2
Missing (%)< 0.1%
Memory size1.1 MiB
0.0
73651 
1.0
 
5

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters220968
Distinct characters3
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
0.0 73651
> 99.9%
1.0 5
 
< 0.1%
(Missing) 2
 
< 0.1%

Length

2023-03-18T21:17:45.118390image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-03-18T21:17:45.333968image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
0.0 73651
> 99.9%
1.0 5
 
< 0.1%

Most occurring characters

ValueCountFrequency (%)
0 147307
66.7%
. 73656
33.3%
1 5
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 147312
66.7%
Other Punctuation 73656
33.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 147307
> 99.9%
1 5
 
< 0.1%
Other Punctuation
ValueCountFrequency (%)
. 73656
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 220968
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 147307
66.7%
. 73656
33.3%
1 5
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 220968
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 147307
66.7%
. 73656
33.3%
1 5
 
< 0.1%
Distinct2
Distinct (%)< 0.1%
Missing2
Missing (%)< 0.1%
Memory size1.1 MiB
0.0
73650 
1.0
 
6

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters220968
Distinct characters3
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
0.0 73650
> 99.9%
1.0 6
 
< 0.1%
(Missing) 2
 
< 0.1%

Length

2023-03-18T21:17:45.411181image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-03-18T21:17:45.503064image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
0.0 73650
> 99.9%
1.0 6
 
< 0.1%

Most occurring characters

ValueCountFrequency (%)
0 147306
66.7%
. 73656
33.3%
1 6
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 147312
66.7%
Other Punctuation 73656
33.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 147306
> 99.9%
1 6
 
< 0.1%
Other Punctuation
ValueCountFrequency (%)
. 73656
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 220968
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 147306
66.7%
. 73656
33.3%
1 6
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 220968
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 147306
66.7%
. 73656
33.3%
1 6
 
< 0.1%

Activity Type_Railway
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing2
Missing (%)< 0.1%
Memory size1.1 MiB
0.0
70444 
1.0
 
3212

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters220968
Distinct characters3
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
0.0 70444
95.6%
1.0 3212
 
4.4%
(Missing) 2
 
< 0.1%

Length

2023-03-18T21:17:45.580787image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-03-18T21:17:45.672174image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
0.0 70444
95.6%
1.0 3212
 
4.4%

Most occurring characters

ValueCountFrequency (%)
0 144100
65.2%
. 73656
33.3%
1 3212
 
1.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 147312
66.7%
Other Punctuation 73656
33.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 144100
97.8%
1 3212
 
2.2%
Other Punctuation
ValueCountFrequency (%)
. 73656
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 220968
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 144100
65.2%
. 73656
33.3%
1 3212
 
1.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 220968
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 144100
65.2%
. 73656
33.3%
1 3212
 
1.5%
Distinct2
Distinct (%)< 0.1%
Missing2
Missing (%)< 0.1%
Memory size1.1 MiB
0.0
73583 
1.0
 
73

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters220968
Distinct characters3
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
0.0 73583
99.9%
1.0 73
 
0.1%
(Missing) 2
 
< 0.1%

Length

2023-03-18T21:17:45.749649image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-03-18T21:17:45.840990image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
0.0 73583
99.9%
1.0 73
 
0.1%

Most occurring characters

ValueCountFrequency (%)
0 147239
66.6%
. 73656
33.3%
1 73
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 147312
66.7%
Other Punctuation 73656
33.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 147239
> 99.9%
1 73
 
< 0.1%
Other Punctuation
ValueCountFrequency (%)
. 73656
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 220968
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 147239
66.6%
. 73656
33.3%
1 73
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 220968
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 147239
66.6%
. 73656
33.3%
1 73
 
< 0.1%
Distinct2
Distinct (%)< 0.1%
Missing2
Missing (%)< 0.1%
Memory size1.1 MiB
0.0
73612 
1.0
 
44

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters220968
Distinct characters3
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
0.0 73612
99.9%
1.0 44
 
0.1%
(Missing) 2
 
< 0.1%

Length

2023-03-18T21:17:45.918009image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-03-18T21:17:46.011372image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
0.0 73612
99.9%
1.0 44
 
0.1%

Most occurring characters

ValueCountFrequency (%)
0 147268
66.6%
. 73656
33.3%
1 44
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 147312
66.7%
Other Punctuation 73656
33.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 147268
> 99.9%
1 44
 
< 0.1%
Other Punctuation
ValueCountFrequency (%)
. 73656
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 220968
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 147268
66.6%
. 73656
33.3%
1 44
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 220968
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 147268
66.6%
. 73656
33.3%
1 44
 
< 0.1%

Activity Type_Roller Sports
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing2
Missing (%)< 0.1%
Memory size1.1 MiB
0.0
73649 
1.0
 
7

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters220968
Distinct characters3
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
0.0 73649
> 99.9%
1.0 7
 
< 0.1%
(Missing) 2
 
< 0.1%

Length

2023-03-18T21:17:46.090925image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-03-18T21:17:46.184144image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
0.0 73649
> 99.9%
1.0 7
 
< 0.1%

Most occurring characters

ValueCountFrequency (%)
0 147305
66.7%
. 73656
33.3%
1 7
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 147312
66.7%
Other Punctuation 73656
33.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 147305
> 99.9%
1 7
 
< 0.1%
Other Punctuation
ValueCountFrequency (%)
. 73656
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 220968
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 147305
66.7%
. 73656
33.3%
1 7
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 220968
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 147305
66.7%
. 73656
33.3%
1 7
 
< 0.1%
Distinct2
Distinct (%)< 0.1%
Missing2
Missing (%)< 0.1%
Memory size1.1 MiB
0.0
73614 
1.0
 
42

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters220968
Distinct characters3
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
0.0 73614
99.9%
1.0 42
 
0.1%
(Missing) 2
 
< 0.1%

Length

2023-03-18T21:17:46.262619image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-03-18T21:17:46.354739image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
0.0 73614
99.9%
1.0 42
 
0.1%

Most occurring characters

ValueCountFrequency (%)
0 147270
66.6%
. 73656
33.3%
1 42
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 147312
66.7%
Other Punctuation 73656
33.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 147270
> 99.9%
1 42
 
< 0.1%
Other Punctuation
ValueCountFrequency (%)
. 73656
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 220968
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 147270
66.6%
. 73656
33.3%
1 42
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 220968
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 147270
66.6%
. 73656
33.3%
1 42
 
< 0.1%
Distinct2
Distinct (%)< 0.1%
Missing2
Missing (%)< 0.1%
Memory size1.1 MiB
0.0
73576 
1.0
 
80

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters220968
Distinct characters3
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
0.0 73576
99.9%
1.0 80
 
0.1%
(Missing) 2
 
< 0.1%

Length

2023-03-18T21:17:46.431801image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-03-18T21:17:46.524516image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
0.0 73576
99.9%
1.0 80
 
0.1%

Most occurring characters

ValueCountFrequency (%)
0 147232
66.6%
. 73656
33.3%
1 80
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 147312
66.7%
Other Punctuation 73656
33.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 147232
99.9%
1 80
 
0.1%
Other Punctuation
ValueCountFrequency (%)
. 73656
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 220968
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 147232
66.6%
. 73656
33.3%
1 80
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 220968
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 147232
66.6%
. 73656
33.3%
1 80
 
< 0.1%

Activity Type_Sail Sports - Wind / Kite Surfing
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing2
Missing (%)< 0.1%
Memory size1.1 MiB
0.0
73655 
1.0
 
1

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters220968
Distinct characters3
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
0.0 73655
> 99.9%
1.0 1
 
< 0.1%
(Missing) 2
 
< 0.1%

Length

2023-03-18T21:17:46.604008image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-03-18T21:17:46.696308image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
0.0 73655
> 99.9%
1.0 1
 
< 0.1%

Most occurring characters

ValueCountFrequency (%)
0 147311
66.7%
. 73656
33.3%
1 1
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 147312
66.7%
Other Punctuation 73656
33.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 147311
> 99.9%
1 1
 
< 0.1%
Other Punctuation
ValueCountFrequency (%)
. 73656
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 220968
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 147311
66.7%
. 73656
33.3%
1 1
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 220968
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 147311
66.7%
. 73656
33.3%
1 1
 
< 0.1%

Activity Type_Scrambling
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing2
Missing (%)< 0.1%
Memory size1.1 MiB
0.0
73653 
1.0
 
3

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters220968
Distinct characters3
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
0.0 73653
> 99.9%
1.0 3
 
< 0.1%
(Missing) 2
 
< 0.1%

Length

2023-03-18T21:17:46.774935image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-03-18T21:17:46.868330image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
0.0 73653
> 99.9%
1.0 3
 
< 0.1%

Most occurring characters

ValueCountFrequency (%)
0 147309
66.7%
. 73656
33.3%
1 3
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 147312
66.7%
Other Punctuation 73656
33.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 147309
> 99.9%
1 3
 
< 0.1%
Other Punctuation
ValueCountFrequency (%)
. 73656
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 220968
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 147309
66.7%
. 73656
33.3%
1 3
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 220968
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 147309
66.7%
. 73656
33.3%
1 3
 
< 0.1%
Distinct2
Distinct (%)< 0.1%
Missing2
Missing (%)< 0.1%
Memory size1.1 MiB
0.0
73594 
1.0
 
62

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters220968
Distinct characters3
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
0.0 73594
99.9%
1.0 62
 
0.1%
(Missing) 2
 
< 0.1%

Length

2023-03-18T21:17:46.946662image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-03-18T21:17:47.039707image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
0.0 73594
99.9%
1.0 62
 
0.1%

Most occurring characters

ValueCountFrequency (%)
0 147250
66.6%
. 73656
33.3%
1 62
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 147312
66.7%
Other Punctuation 73656
33.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 147250
> 99.9%
1 62
 
< 0.1%
Other Punctuation
ValueCountFrequency (%)
. 73656
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 220968
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 147250
66.6%
. 73656
33.3%
1 62
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 220968
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 147250
66.6%
. 73656
33.3%
1 62
 
< 0.1%
Distinct2
Distinct (%)< 0.1%
Missing2
Missing (%)< 0.1%
Memory size1.1 MiB
0.0
73617 
1.0
 
39

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters220968
Distinct characters3
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
0.0 73617
99.9%
1.0 39
 
0.1%
(Missing) 2
 
< 0.1%

Length

2023-03-18T21:17:47.118822image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-03-18T21:17:47.212157image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
0.0 73617
99.9%
1.0 39
 
0.1%

Most occurring characters

ValueCountFrequency (%)
0 147273
66.6%
. 73656
33.3%
1 39
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 147312
66.7%
Other Punctuation 73656
33.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 147273
> 99.9%
1 39
 
< 0.1%
Other Punctuation
ValueCountFrequency (%)
. 73656
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 220968
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 147273
66.6%
. 73656
33.3%
1 39
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 220968
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 147273
66.6%
. 73656
33.3%
1 39
 
< 0.1%
Distinct2
Distinct (%)< 0.1%
Missing2
Missing (%)< 0.1%
Memory size1.1 MiB
0.0
73605 
1.0
 
51

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters220968
Distinct characters3
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
0.0 73605
99.9%
1.0 51
 
0.1%
(Missing) 2
 
< 0.1%

Length

2023-03-18T21:17:47.289600image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-03-18T21:17:47.381191image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
0.0 73605
99.9%
1.0 51
 
0.1%

Most occurring characters

ValueCountFrequency (%)
0 147261
66.6%
. 73656
33.3%
1 51
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 147312
66.7%
Other Punctuation 73656
33.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 147261
> 99.9%
1 51
 
< 0.1%
Other Punctuation
ValueCountFrequency (%)
. 73656
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 220968
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 147261
66.6%
. 73656
33.3%
1 51
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 220968
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 147261
66.6%
. 73656
33.3%
1 51
 
< 0.1%

Activity Type_Skiing/Boarding - Ski Resort Out of Bounds
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing2
Missing (%)< 0.1%
Memory size1.1 MiB
0.0
73653 
1.0
 
3

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters220968
Distinct characters3
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
0.0 73653
> 99.9%
1.0 3
 
< 0.1%
(Missing) 2
 
< 0.1%

Length

2023-03-18T21:17:47.459871image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-03-18T21:17:47.552761image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
0.0 73653
> 99.9%
1.0 3
 
< 0.1%

Most occurring characters

ValueCountFrequency (%)
0 147309
66.7%
. 73656
33.3%
1 3
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 147312
66.7%
Other Punctuation 73656
33.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 147309
> 99.9%
1 3
 
< 0.1%
Other Punctuation
ValueCountFrequency (%)
. 73656
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 220968
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 147309
66.7%
. 73656
33.3%
1 3
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 220968
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 147309
66.7%
. 73656
33.3%
1 3
 
< 0.1%
Distinct2
Distinct (%)< 0.1%
Missing2
Missing (%)< 0.1%
Memory size1.1 MiB
0.0
73649 
1.0
 
7

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters220968
Distinct characters3
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
0.0 73649
> 99.9%
1.0 7
 
< 0.1%
(Missing) 2
 
< 0.1%

Length

2023-03-18T21:17:47.631994image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-03-18T21:17:47.723772image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
0.0 73649
> 99.9%
1.0 7
 
< 0.1%

Most occurring characters

ValueCountFrequency (%)
0 147305
66.7%
. 73656
33.3%
1 7
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 147312
66.7%
Other Punctuation 73656
33.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 147305
> 99.9%
1 7
 
< 0.1%
Other Punctuation
ValueCountFrequency (%)
. 73656
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 220968
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 147305
66.7%
. 73656
33.3%
1 7
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 220968
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 147305
66.7%
. 73656
33.3%
1 7
 
< 0.1%

Activity Type_Snowmobiling
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing2
Missing (%)< 0.1%
Memory size1.1 MiB
0.0
73655 
1.0
 
1

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters220968
Distinct characters3
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
0.0 73655
> 99.9%
1.0 1
 
< 0.1%
(Missing) 2
 
< 0.1%

Length

2023-03-18T21:17:47.801344image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-03-18T21:17:47.893040image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
0.0 73655
> 99.9%
1.0 1
 
< 0.1%

Most occurring characters

ValueCountFrequency (%)
0 147311
66.7%
. 73656
33.3%
1 1
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 147312
66.7%
Other Punctuation 73656
33.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 147311
> 99.9%
1 1
 
< 0.1%
Other Punctuation
ValueCountFrequency (%)
. 73656
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 220968
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 147311
66.7%
. 73656
33.3%
1 1
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 220968
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 147311
66.7%
. 73656
33.3%
1 1
 
< 0.1%

Activity Type_Snowshoeing
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing2
Missing (%)< 0.1%
Memory size1.1 MiB
0.0
73646 
1.0
 
10

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters220968
Distinct characters3
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
0.0 73646
> 99.9%
1.0 10
 
< 0.1%
(Missing) 2
 
< 0.1%

Length

2023-03-18T21:17:47.977356image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-03-18T21:17:48.075778image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
0.0 73646
> 99.9%
1.0 10
 
< 0.1%

Most occurring characters

ValueCountFrequency (%)
0 147302
66.7%
. 73656
33.3%
1 10
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 147312
66.7%
Other Punctuation 73656
33.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 147302
> 99.9%
1 10
 
< 0.1%
Other Punctuation
ValueCountFrequency (%)
. 73656
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 220968
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 147302
66.7%
. 73656
33.3%
1 10
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 220968
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 147302
66.7%
. 73656
33.3%
1 10
 
< 0.1%
Distinct2
Distinct (%)< 0.1%
Missing2
Missing (%)< 0.1%
Memory size1.1 MiB
0.0
73638 
1.0
 
18

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters220968
Distinct characters3
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
0.0 73638
> 99.9%
1.0 18
 
< 0.1%
(Missing) 2
 
< 0.1%

Length

2023-03-18T21:17:48.280938image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-03-18T21:17:48.373080image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
0.0 73638
> 99.9%
1.0 18
 
< 0.1%

Most occurring characters

ValueCountFrequency (%)
0 147294
66.7%
. 73656
33.3%
1 18
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 147312
66.7%
Other Punctuation 73656
33.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 147294
> 99.9%
1 18
 
< 0.1%
Other Punctuation
ValueCountFrequency (%)
. 73656
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 220968
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 147294
66.7%
. 73656
33.3%
1 18
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 220968
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 147294
66.7%
. 73656
33.3%
1 18
 
< 0.1%
Distinct2
Distinct (%)< 0.1%
Missing2
Missing (%)< 0.1%
Memory size1.1 MiB
0.0
73644 
1.0
 
12

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters220968
Distinct characters3
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
0.0 73644
> 99.9%
1.0 12
 
< 0.1%
(Missing) 2
 
< 0.1%

Length

2023-03-18T21:17:48.450965image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-03-18T21:17:48.543936image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
0.0 73644
> 99.9%
1.0 12
 
< 0.1%

Most occurring characters

ValueCountFrequency (%)
0 147300
66.7%
. 73656
33.3%
1 12
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 147312
66.7%
Other Punctuation 73656
33.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 147300
> 99.9%
1 12
 
< 0.1%
Other Punctuation
ValueCountFrequency (%)
. 73656
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 220968
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 147300
66.7%
. 73656
33.3%
1 12
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 220968
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 147300
66.7%
. 73656
33.3%
1 12
 
< 0.1%
Distinct2
Distinct (%)< 0.1%
Missing2
Missing (%)< 0.1%
Memory size1.1 MiB
0.0
70437 
1.0
 
3219

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters220968
Distinct characters3
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
0.0 70437
95.6%
1.0 3219
 
4.4%
(Missing) 2
 
< 0.1%

Length

2023-03-18T21:17:48.623534image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-03-18T21:17:48.715360image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
0.0 70437
95.6%
1.0 3219
 
4.4%

Most occurring characters

ValueCountFrequency (%)
0 144093
65.2%
. 73656
33.3%
1 3219
 
1.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 147312
66.7%
Other Punctuation 73656
33.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 144093
97.8%
1 3219
 
2.2%
Other Punctuation
ValueCountFrequency (%)
. 73656
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 220968
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 144093
65.2%
. 73656
33.3%
1 3219
 
1.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 220968
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 144093
65.2%
. 73656
33.3%
1 3219
 
1.5%

Activity Type_Surfing
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing2
Missing (%)< 0.1%
Memory size1.1 MiB
0.0
73649 
1.0
 
7

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters220968
Distinct characters3
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
0.0 73649
> 99.9%
1.0 7
 
< 0.1%
(Missing) 2
 
< 0.1%

Length

2023-03-18T21:17:48.792969image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-03-18T21:17:48.884328image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
0.0 73649
> 99.9%
1.0 7
 
< 0.1%

Most occurring characters

ValueCountFrequency (%)
0 147305
66.7%
. 73656
33.3%
1 7
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 147312
66.7%
Other Punctuation 73656
33.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 147305
> 99.9%
1 7
 
< 0.1%
Other Punctuation
ValueCountFrequency (%)
. 73656
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 220968
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 147305
66.7%
. 73656
33.3%
1 7
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 220968
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 147305
66.7%
. 73656
33.3%
1 7
 
< 0.1%

Activity Type_Swimming - Cliff Jumping
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing2
Missing (%)< 0.1%
Memory size1.1 MiB
0.0
73655 
1.0
 
1

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters220968
Distinct characters3
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
0.0 73655
> 99.9%
1.0 1
 
< 0.1%
(Missing) 2
 
< 0.1%

Length

2023-03-18T21:17:48.961669image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-03-18T21:17:49.053205image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
0.0 73655
> 99.9%
1.0 1
 
< 0.1%

Most occurring characters

ValueCountFrequency (%)
0 147311
66.7%
. 73656
33.3%
1 1
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 147312
66.7%
Other Punctuation 73656
33.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 147311
> 99.9%
1 1
 
< 0.1%
Other Punctuation
ValueCountFrequency (%)
. 73656
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 220968
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 147311
66.7%
. 73656
33.3%
1 1
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 220968
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 147311
66.7%
. 73656
33.3%
1 1
 
< 0.1%

Activity Type_Swimming - Coastal
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing2
Missing (%)< 0.1%
Memory size1.1 MiB
0.0
73655 
1.0
 
1

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters220968
Distinct characters3
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
0.0 73655
> 99.9%
1.0 1
 
< 0.1%
(Missing) 2
 
< 0.1%

Length

2023-03-18T21:17:49.130278image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-03-18T21:17:49.221766image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
0.0 73655
> 99.9%
1.0 1
 
< 0.1%

Most occurring characters

ValueCountFrequency (%)
0 147311
66.7%
. 73656
33.3%
1 1
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 147312
66.7%
Other Punctuation 73656
33.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 147311
> 99.9%
1 1
 
< 0.1%
Other Punctuation
ValueCountFrequency (%)
. 73656
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 220968
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 147311
66.7%
. 73656
33.3%
1 1
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 220968
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 147311
66.7%
. 73656
33.3%
1 1
 
< 0.1%
Distinct2
Distinct (%)< 0.1%
Missing2
Missing (%)< 0.1%
Memory size1.1 MiB
0.0
73644 
1.0
 
12

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters220968
Distinct characters3
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
0.0 73644
> 99.9%
1.0 12
 
< 0.1%
(Missing) 2
 
< 0.1%

Length

2023-03-18T21:17:49.299142image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-03-18T21:17:49.390612image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
0.0 73644
> 99.9%
1.0 12
 
< 0.1%

Most occurring characters

ValueCountFrequency (%)
0 147300
66.7%
. 73656
33.3%
1 12
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 147312
66.7%
Other Punctuation 73656
33.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 147300
> 99.9%
1 12
 
< 0.1%
Other Punctuation
ValueCountFrequency (%)
. 73656
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 220968
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 147300
66.7%
. 73656
33.3%
1 12
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 220968
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 147300
66.7%
. 73656
33.3%
1 12
 
< 0.1%
Distinct2
Distinct (%)< 0.1%
Missing2
Missing (%)< 0.1%
Memory size1.1 MiB
0.0
73632 
1.0
 
24

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters220968
Distinct characters3
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
0.0 73632
> 99.9%
1.0 24
 
< 0.1%
(Missing) 2
 
< 0.1%

Length

2023-03-18T21:17:49.468309image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-03-18T21:17:49.561741image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
0.0 73632
> 99.9%
1.0 24
 
< 0.1%

Most occurring characters

ValueCountFrequency (%)
0 147288
66.7%
. 73656
33.3%
1 24
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 147312
66.7%
Other Punctuation 73656
33.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 147288
> 99.9%
1 24
 
< 0.1%
Other Punctuation
ValueCountFrequency (%)
. 73656
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 220968
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 147288
66.7%
. 73656
33.3%
1 24
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 220968
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 147288
66.7%
. 73656
33.3%
1 24
 
< 0.1%

Activity Type_Swimming - Swiftwater
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing2
Missing (%)< 0.1%
Memory size1.1 MiB
0.0
73647 
1.0
 
9

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters220968
Distinct characters3
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
0.0 73647
> 99.9%
1.0 9
 
< 0.1%
(Missing) 2
 
< 0.1%

Length

2023-03-18T21:17:49.639589image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-03-18T21:17:49.731390image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
0.0 73647
> 99.9%
1.0 9
 
< 0.1%

Most occurring characters

ValueCountFrequency (%)
0 147303
66.7%
. 73656
33.3%
1 9
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 147312
66.7%
Other Punctuation 73656
33.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 147303
> 99.9%
1 9
 
< 0.1%
Other Punctuation
ValueCountFrequency (%)
. 73656
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 220968
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 147303
66.7%
. 73656
33.3%
1 9
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 220968
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 147303
66.7%
. 73656
33.3%
1 9
 
< 0.1%
Distinct2
Distinct (%)< 0.1%
Missing2
Missing (%)< 0.1%
Memory size1.1 MiB
0.0
60684 
1.0
12972 

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters220968
Distinct characters3
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
0.0 60684
82.4%
1.0 12972
 
17.6%
(Missing) 2
 
< 0.1%

Length

2023-03-18T21:17:49.810423image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-03-18T21:17:49.903963image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
0.0 60684
82.4%
1.0 12972
 
17.6%

Most occurring characters

ValueCountFrequency (%)
0 134340
60.8%
. 73656
33.3%
1 12972
 
5.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 147312
66.7%
Other Punctuation 73656
33.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 134340
91.2%
1 12972
 
8.8%
Other Punctuation
ValueCountFrequency (%)
. 73656
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 220968
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 134340
60.8%
. 73656
33.3%
1 12972
 
5.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 220968
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 134340
60.8%
. 73656
33.3%
1 12972
 
5.9%
Distinct2
Distinct (%)< 0.1%
Missing2
Missing (%)< 0.1%
Memory size1.1 MiB
0.0
73619 
1.0
 
37

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters220968
Distinct characters3
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
0.0 73619
99.9%
1.0 37
 
0.1%
(Missing) 2
 
< 0.1%

Length

2023-03-18T21:17:49.986012image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-03-18T21:17:50.078124image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
0.0 73619
99.9%
1.0 37
 
0.1%

Most occurring characters

ValueCountFrequency (%)
0 147275
66.6%
. 73656
33.3%
1 37
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 147312
66.7%
Other Punctuation 73656
33.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 147275
> 99.9%
1 37
 
< 0.1%
Other Punctuation
ValueCountFrequency (%)
. 73656
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 220968
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 147275
66.6%
. 73656
33.3%
1 37
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 220968
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 147275
66.6%
. 73656
33.3%
1 37
 
< 0.1%

Activity Type_Tubing / River Drifting
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing2
Missing (%)< 0.1%
Memory size1.1 MiB
0.0
73654 
1.0
 
2

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters220968
Distinct characters3
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
0.0 73654
> 99.9%
1.0 2
 
< 0.1%
(Missing) 2
 
< 0.1%

Length

2023-03-18T21:17:50.156426image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-03-18T21:17:50.249936image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
0.0 73654
> 99.9%
1.0 2
 
< 0.1%

Most occurring characters

ValueCountFrequency (%)
0 147310
66.7%
. 73656
33.3%
1 2
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 147312
66.7%
Other Punctuation 73656
33.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 147310
> 99.9%
1 2
 
< 0.1%
Other Punctuation
ValueCountFrequency (%)
. 73656
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 220968
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 147310
66.7%
. 73656
33.3%
1 2
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 220968
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 147310
66.7%
. 73656
33.3%
1 2
 
< 0.1%
Distinct2
Distinct (%)< 0.1%
Missing2
Missing (%)< 0.1%
Memory size1.1 MiB
0.0
73488 
1.0
 
168

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters220968
Distinct characters3
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
0.0 73488
99.8%
1.0 168
 
0.2%
(Missing) 2
 
< 0.1%

Length

2023-03-18T21:17:50.328159image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-03-18T21:17:50.419936image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
0.0 73488
99.8%
1.0 168
 
0.2%

Most occurring characters

ValueCountFrequency (%)
0 147144
66.6%
. 73656
33.3%
1 168
 
0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 147312
66.7%
Other Punctuation 73656
33.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 147144
99.9%
1 168
 
0.1%
Other Punctuation
ValueCountFrequency (%)
. 73656
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 220968
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 147144
66.6%
. 73656
33.3%
1 168
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 220968
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 147144
66.6%
. 73656
33.3%
1 168
 
0.1%

Activity Type_Via-Ferrata
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing2
Missing (%)< 0.1%
Memory size1.1 MiB
0.0
73655 
1.0
 
1

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters220968
Distinct characters3
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
0.0 73655
> 99.9%
1.0 1
 
< 0.1%
(Missing) 2
 
< 0.1%

Length

2023-03-18T21:17:50.497887image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-03-18T21:17:50.589726image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
0.0 73655
> 99.9%
1.0 1
 
< 0.1%

Most occurring characters

ValueCountFrequency (%)
0 147311
66.7%
. 73656
33.3%
1 1
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 147312
66.7%
Other Punctuation 73656
33.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 147311
> 99.9%
1 1
 
< 0.1%
Other Punctuation
ValueCountFrequency (%)
. 73656
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 220968
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 147311
66.7%
. 73656
33.3%
1 1
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 220968
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 147311
66.7%
. 73656
33.3%
1 1
 
< 0.1%

Activity Type_nan
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing2
Missing (%)< 0.1%
Memory size1.1 MiB
0.0
67366 
1.0
 
6290

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters220968
Distinct characters3
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1.0
2nd row1.0
3rd row1.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
0.0 67366
91.5%
1.0 6290
 
8.5%
(Missing) 2
 
< 0.1%

Length

2023-03-18T21:17:50.668433image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-03-18T21:17:50.761743image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
0.0 67366
91.5%
1.0 6290
 
8.5%

Most occurring characters

ValueCountFrequency (%)
0 141022
63.8%
. 73656
33.3%
1 6290
 
2.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 147312
66.7%
Other Punctuation 73656
33.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 141022
95.7%
1 6290
 
4.3%
Other Punctuation
ValueCountFrequency (%)
. 73656
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 220968
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 141022
63.8%
. 73656
33.3%
1 6290
 
2.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 220968
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 141022
63.8%
. 73656
33.3%
1 6290
 
2.8%

Response Type_
Categorical

HIGH CORRELATION  IMBALANCE  MISSING 

Distinct2
Distinct (%)< 0.1%
Missing1462
Missing (%)2.0%
Memory size1.1 MiB
0.0
72193 
1.0
 
3

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters216588
Distinct characters3
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
0.0 72193
98.0%
1.0 3
 
< 0.1%
(Missing) 1462
 
2.0%

Length

2023-03-18T21:17:50.841760image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-03-18T21:17:50.933241image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
0.0 72193
> 99.9%
1.0 3
 
< 0.1%

Most occurring characters

ValueCountFrequency (%)
0 144389
66.7%
. 72196
33.3%
1 3
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 144392
66.7%
Other Punctuation 72196
33.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 144389
> 99.9%
1 3
 
< 0.1%
Other Punctuation
ValueCountFrequency (%)
. 72196
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 216588
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 144389
66.7%
. 72196
33.3%
1 3
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 216588
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 144389
66.7%
. 72196
33.3%
1 3
 
< 0.1%

Response Type_Assist Visitor
Categorical

IMBALANCE  MISSING 

Distinct2
Distinct (%)< 0.1%
Missing1462
Missing (%)2.0%
Memory size1.1 MiB
0.0
71943 
1.0
 
253

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters216588
Distinct characters3
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
0.0 71943
97.7%
1.0 253
 
0.3%
(Missing) 1462
 
2.0%

Length

2023-03-18T21:17:51.010777image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-03-18T21:17:51.229632image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
0.0 71943
99.6%
1.0 253
 
0.4%

Most occurring characters

ValueCountFrequency (%)
0 144139
66.5%
. 72196
33.3%
1 253
 
0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 144392
66.7%
Other Punctuation 72196
33.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 144139
99.8%
1 253
 
0.2%
Other Punctuation
ValueCountFrequency (%)
. 72196
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 216588
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 144139
66.5%
. 72196
33.3%
1 253
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 216588
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 144139
66.5%
. 72196
33.3%
1 253
 
0.1%

Response Type_Assist other Agency
Categorical

IMBALANCE  MISSING 

Distinct2
Distinct (%)< 0.1%
Missing1462
Missing (%)2.0%
Memory size1.1 MiB
0.0
71884 
1.0
 
312

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters216588
Distinct characters3
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
0.0 71884
97.6%
1.0 312
 
0.4%
(Missing) 1462
 
2.0%

Length

2023-03-18T21:17:51.306604image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-03-18T21:17:51.398099image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
0.0 71884
99.6%
1.0 312
 
0.4%

Most occurring characters

ValueCountFrequency (%)
0 144080
66.5%
. 72196
33.3%
1 312
 
0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 144392
66.7%
Other Punctuation 72196
33.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 144080
99.8%
1 312
 
0.2%
Other Punctuation
ValueCountFrequency (%)
. 72196
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 216588
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 144080
66.5%
. 72196
33.3%
1 312
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 216588
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 144080
66.5%
. 72196
33.3%
1 312
 
0.1%

Response Type_Assist other Field Unit
Categorical

IMBALANCE  MISSING 

Distinct2
Distinct (%)< 0.1%
Missing1462
Missing (%)2.0%
Memory size1.1 MiB
0.0
72186 
1.0
 
10

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters216588
Distinct characters3
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
0.0 72186
98.0%
1.0 10
 
< 0.1%
(Missing) 1462
 
2.0%

Length

2023-03-18T21:17:51.475567image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-03-18T21:17:51.567166image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
0.0 72186
> 99.9%
1.0 10
 
< 0.1%

Most occurring characters

ValueCountFrequency (%)
0 144382
66.7%
. 72196
33.3%
1 10
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 144392
66.7%
Other Punctuation 72196
33.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 144382
> 99.9%
1 10
 
< 0.1%
Other Punctuation
ValueCountFrequency (%)
. 72196
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 216588
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 144382
66.7%
. 72196
33.3%
1 10
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 216588
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 144382
66.7%
. 72196
33.3%
1 10
 
< 0.1%

Response Type_Attractant Management
Categorical

IMBALANCE  MISSING 

Distinct2
Distinct (%)< 0.1%
Missing1462
Missing (%)2.0%
Memory size1.1 MiB
0.0
71786 
1.0
 
410

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters216588
Distinct characters3
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
0.0 71786
97.5%
1.0 410
 
0.6%
(Missing) 1462
 
2.0%

Length

2023-03-18T21:17:51.644531image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-03-18T21:17:51.736152image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
0.0 71786
99.4%
1.0 410
 
0.6%

Most occurring characters

ValueCountFrequency (%)
0 143982
66.5%
. 72196
33.3%
1 410
 
0.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 144392
66.7%
Other Punctuation 72196
33.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 143982
99.7%
1 410
 
0.3%
Other Punctuation
ValueCountFrequency (%)
. 72196
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 216588
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 143982
66.5%
. 72196
33.3%
1 410
 
0.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 216588
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 143982
66.5%
. 72196
33.3%
1 410
 
0.2%

Response Type_Aversive Conditioning
Categorical

IMBALANCE  MISSING 

Distinct2
Distinct (%)< 0.1%
Missing1462
Missing (%)2.0%
Memory size1.1 MiB
0.0
72049 
1.0
 
147

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters216588
Distinct characters3
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
0.0 72049
97.8%
1.0 147
 
0.2%
(Missing) 1462
 
2.0%

Length

2023-03-18T21:17:51.813433image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-03-18T21:17:51.905114image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
0.0 72049
99.8%
1.0 147
 
0.2%

Most occurring characters

ValueCountFrequency (%)
0 144245
66.6%
. 72196
33.3%
1 147
 
0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 144392
66.7%
Other Punctuation 72196
33.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 144245
99.9%
1 147
 
0.1%
Other Punctuation
ValueCountFrequency (%)
. 72196
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 216588
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 144245
66.6%
. 72196
33.3%
1 147
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 216588
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 144245
66.6%
. 72196
33.3%
1 147
 
0.1%

Response Type_Capture and transport to captivity
Categorical

IMBALANCE  MISSING 

Distinct2
Distinct (%)< 0.1%
Missing1462
Missing (%)2.0%
Memory size1.1 MiB
0.0
72128 
1.0
 
68

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters216588
Distinct characters3
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
0.0 72128
97.9%
1.0 68
 
0.1%
(Missing) 1462
 
2.0%

Length

2023-03-18T21:17:51.983720image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-03-18T21:17:52.075412image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
0.0 72128
99.9%
1.0 68
 
0.1%

Most occurring characters

ValueCountFrequency (%)
0 144324
66.6%
. 72196
33.3%
1 68
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 144392
66.7%
Other Punctuation 72196
33.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 144324
> 99.9%
1 68
 
< 0.1%
Other Punctuation
ValueCountFrequency (%)
. 72196
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 216588
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 144324
66.6%
. 72196
33.3%
1 68
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 216588
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 144324
66.6%
. 72196
33.3%
1 68
 
< 0.1%

Response Type_Clean Up
Categorical

IMBALANCE  MISSING 

Distinct2
Distinct (%)< 0.1%
Missing1462
Missing (%)2.0%
Memory size1.1 MiB
0.0
71133 
1.0
 
1063

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters216588
Distinct characters3
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
0.0 71133
96.6%
1.0 1063
 
1.4%
(Missing) 1462
 
2.0%

Length

2023-03-18T21:17:52.152533image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-03-18T21:17:52.245222image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
0.0 71133
98.5%
1.0 1063
 
1.5%

Most occurring characters

ValueCountFrequency (%)
0 143329
66.2%
. 72196
33.3%
1 1063
 
0.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 144392
66.7%
Other Punctuation 72196
33.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 143329
99.3%
1 1063
 
0.7%
Other Punctuation
ValueCountFrequency (%)
. 72196
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 216588
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 143329
66.2%
. 72196
33.3%
1 1063
 
0.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 216588
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 143329
66.2%
. 72196
33.3%
1 1063
 
0.5%

Response Type_Close Area
Categorical

IMBALANCE  MISSING 

Distinct2
Distinct (%)< 0.1%
Missing1462
Missing (%)2.0%
Memory size1.1 MiB
0.0
71166 
1.0
 
1030

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters216588
Distinct characters3
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
0.0 71166
96.6%
1.0 1030
 
1.4%
(Missing) 1462
 
2.0%

Length

2023-03-18T21:17:52.322270image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-03-18T21:17:52.415744image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
0.0 71166
98.6%
1.0 1030
 
1.4%

Most occurring characters

ValueCountFrequency (%)
0 143362
66.2%
. 72196
33.3%
1 1030
 
0.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 144392
66.7%
Other Punctuation 72196
33.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 143362
99.3%
1 1030
 
0.7%
Other Punctuation
ValueCountFrequency (%)
. 72196
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 216588
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 143362
66.2%
. 72196
33.3%
1 1030
 
0.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 216588
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 143362
66.2%
. 72196
33.3%
1 1030
 
0.5%

Response Type_Close Road
Categorical

HIGH CORRELATION  IMBALANCE  MISSING 

Distinct2
Distinct (%)< 0.1%
Missing1462
Missing (%)2.0%
Memory size1.1 MiB
0.0
71998 
1.0
 
198

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters216588
Distinct characters3
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
0.0 71998
97.7%
1.0 198
 
0.3%
(Missing) 1462
 
2.0%

Length

2023-03-18T21:17:52.493953image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-03-18T21:17:52.587451image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
0.0 71998
99.7%
1.0 198
 
0.3%

Most occurring characters

ValueCountFrequency (%)
0 144194
66.6%
. 72196
33.3%
1 198
 
0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 144392
66.7%
Other Punctuation 72196
33.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 144194
99.9%
1 198
 
0.1%
Other Punctuation
ValueCountFrequency (%)
. 72196
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 216588
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 144194
66.6%
. 72196
33.3%
1 198
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 216588
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 144194
66.6%
. 72196
33.3%
1 198
 
0.1%

Response Type_Collar
Categorical

IMBALANCE  MISSING 

Distinct2
Distinct (%)< 0.1%
Missing1462
Missing (%)2.0%
Memory size1.1 MiB
0.0
72160 
1.0
 
36

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters216588
Distinct characters3
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
0.0 72160
98.0%
1.0 36
 
< 0.1%
(Missing) 1462
 
2.0%

Length

2023-03-18T21:17:52.666018image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-03-18T21:17:52.757874image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
0.0 72160
> 99.9%
1.0 36
 
< 0.1%

Most occurring characters

ValueCountFrequency (%)
0 144356
66.7%
. 72196
33.3%
1 36
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 144392
66.7%
Other Punctuation 72196
33.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 144356
> 99.9%
1 36
 
< 0.1%
Other Punctuation
ValueCountFrequency (%)
. 72196
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 216588
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 144356
66.7%
. 72196
33.3%
1 36
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 216588
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 144356
66.7%
. 72196
33.3%
1 36
 
< 0.1%

Response Type_Collect Sample
Categorical

HIGH CORRELATION  IMBALANCE  MISSING 

Distinct2
Distinct (%)< 0.1%
Missing1462
Missing (%)2.0%
Memory size1.1 MiB
0.0
71598 
1.0
 
598

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters216588
Distinct characters3
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
0.0 71598
97.2%
1.0 598
 
0.8%
(Missing) 1462
 
2.0%

Length

2023-03-18T21:17:52.835097image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-03-18T21:17:52.926548image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
0.0 71598
99.2%
1.0 598
 
0.8%

Most occurring characters

ValueCountFrequency (%)
0 143794
66.4%
. 72196
33.3%
1 598
 
0.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 144392
66.7%
Other Punctuation 72196
33.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 143794
99.6%
1 598
 
0.4%
Other Punctuation
ValueCountFrequency (%)
. 72196
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 216588
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 143794
66.4%
. 72196
33.3%
1 598
 
0.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 216588
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 143794
66.4%
. 72196
33.3%
1 598
 
0.3%

Response Type_Cull
Categorical

HIGH CORRELATION  IMBALANCE  MISSING 

Distinct2
Distinct (%)< 0.1%
Missing1462
Missing (%)2.0%
Memory size1.1 MiB
0.0
72017 
1.0
 
179

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters216588
Distinct characters3
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
0.0 72017
97.8%
1.0 179
 
0.2%
(Missing) 1462
 
2.0%

Length

2023-03-18T21:17:53.003836image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-03-18T21:17:53.098126image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
0.0 72017
99.8%
1.0 179
 
0.2%

Most occurring characters

ValueCountFrequency (%)
0 144213
66.6%
. 72196
33.3%
1 179
 
0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 144392
66.7%
Other Punctuation 72196
33.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 144213
99.9%
1 179
 
0.1%
Other Punctuation
ValueCountFrequency (%)
. 72196
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 216588
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 144213
66.6%
. 72196
33.3%
1 179
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 216588
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 144213
66.6%
. 72196
33.3%
1 179
 
0.1%

Response Type_Destroy Animal
Categorical

HIGH CORRELATION  IMBALANCE  MISSING 

Distinct2
Distinct (%)< 0.1%
Missing1462
Missing (%)2.0%
Memory size1.1 MiB
0.0
71397 
1.0
 
799

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters216588
Distinct characters3
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
0.0 71397
96.9%
1.0 799
 
1.1%
(Missing) 1462
 
2.0%

Length

2023-03-18T21:17:53.181295image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-03-18T21:17:53.275316image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
0.0 71397
98.9%
1.0 799
 
1.1%

Most occurring characters

ValueCountFrequency (%)
0 143593
66.3%
. 72196
33.3%
1 799
 
0.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 144392
66.7%
Other Punctuation 72196
33.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 143593
99.4%
1 799
 
0.6%
Other Punctuation
ValueCountFrequency (%)
. 72196
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 216588
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 143593
66.3%
. 72196
33.3%
1 799
 
0.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 216588
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 143593
66.3%
. 72196
33.3%
1 799
 
0.4%

Response Type_Disentangle
Categorical

IMBALANCE  MISSING 

Distinct2
Distinct (%)< 0.1%
Missing1462
Missing (%)2.0%
Memory size1.1 MiB
0.0
72063 
1.0
 
133

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters216588
Distinct characters3
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
0.0 72063
97.8%
1.0 133
 
0.2%
(Missing) 1462
 
2.0%

Length

2023-03-18T21:17:53.355779image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-03-18T21:17:53.450136image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
0.0 72063
99.8%
1.0 133
 
0.2%

Most occurring characters

ValueCountFrequency (%)
0 144259
66.6%
. 72196
33.3%
1 133
 
0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 144392
66.7%
Other Punctuation 72196
33.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 144259
99.9%
1 133
 
0.1%
Other Punctuation
ValueCountFrequency (%)
. 72196
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 216588
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 144259
66.6%
. 72196
33.3%
1 133
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 216588
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 144259
66.6%
. 72196
33.3%
1 133
 
0.1%

Response Type_Dispatch other Agency
Categorical

IMBALANCE  MISSING 

Distinct2
Distinct (%)< 0.1%
Missing1462
Missing (%)2.0%
Memory size1.1 MiB
0.0
72050 
1.0
 
146

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters216588
Distinct characters3
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
0.0 72050
97.8%
1.0 146
 
0.2%
(Missing) 1462
 
2.0%

Length

2023-03-18T21:17:53.528764image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-03-18T21:17:53.621845image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
0.0 72050
99.8%
1.0 146
 
0.2%

Most occurring characters

ValueCountFrequency (%)
0 144246
66.6%
. 72196
33.3%
1 146
 
0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 144392
66.7%
Other Punctuation 72196
33.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 144246
99.9%
1 146
 
0.1%
Other Punctuation
ValueCountFrequency (%)
. 72196
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 216588
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 144246
66.6%
. 72196
33.3%
1 146
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 216588
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 144246
66.6%
. 72196
33.3%
1 146
 
0.1%

Response Type_Disperse Wildlife Jam
Categorical

IMBALANCE  MISSING 

Distinct2
Distinct (%)< 0.1%
Missing1462
Missing (%)2.0%
Memory size1.1 MiB
0.0
68968 
1.0
 
3228

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters216588
Distinct characters3
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
0.0 68968
93.6%
1.0 3228
 
4.4%
(Missing) 1462
 
2.0%

Length

2023-03-18T21:17:53.701537image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-03-18T21:17:53.794852image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
0.0 68968
95.5%
1.0 3228
 
4.5%

Most occurring characters

ValueCountFrequency (%)
0 141164
65.2%
. 72196
33.3%
1 3228
 
1.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 144392
66.7%
Other Punctuation 72196
33.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 141164
97.8%
1 3228
 
2.2%
Other Punctuation
ValueCountFrequency (%)
. 72196
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 216588
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 141164
65.2%
. 72196
33.3%
1 3228
 
1.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 216588
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 141164
65.2%
. 72196
33.3%
1 3228
 
1.5%

Response Type_Dispose Carcass
Categorical

HIGH CORRELATION  IMBALANCE  MISSING 

Distinct2
Distinct (%)< 0.1%
Missing1462
Missing (%)2.0%
Memory size1.1 MiB
0.0
67265 
1.0
 
4931

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters216588
Distinct characters3
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1.0
2nd row1.0
3rd row1.0
4th row1.0
5th row1.0

Common Values

ValueCountFrequency (%)
0.0 67265
91.3%
1.0 4931
 
6.7%
(Missing) 1462
 
2.0%

Length

2023-03-18T21:17:53.878402image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-03-18T21:17:53.980277image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
0.0 67265
93.2%
1.0 4931
 
6.8%

Most occurring characters

ValueCountFrequency (%)
0 139461
64.4%
. 72196
33.3%
1 4931
 
2.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 144392
66.7%
Other Punctuation 72196
33.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 139461
96.6%
1 4931
 
3.4%
Other Punctuation
ValueCountFrequency (%)
. 72196
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 216588
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 139461
64.4%
. 72196
33.3%
1 4931
 
2.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 216588
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 139461
64.4%
. 72196
33.3%
1 4931
 
2.3%

Response Type_Ear Tag
Categorical

IMBALANCE  MISSING 

Distinct2
Distinct (%)< 0.1%
Missing1462
Missing (%)2.0%
Memory size1.1 MiB
0.0
72042 
1.0
 
154

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters216588
Distinct characters3
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
0.0 72042
97.8%
1.0 154
 
0.2%
(Missing) 1462
 
2.0%

Length

2023-03-18T21:17:54.200209image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-03-18T21:17:54.291577image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
0.0 72042
99.8%
1.0 154
 
0.2%

Most occurring characters

ValueCountFrequency (%)
0 144238
66.6%
. 72196
33.3%
1 154
 
0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 144392
66.7%
Other Punctuation 72196
33.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 144238
99.9%
1 154
 
0.1%
Other Punctuation
ValueCountFrequency (%)
. 72196
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 216588
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 144238
66.6%
. 72196
33.3%
1 154
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 216588
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 144238
66.6%
. 72196
33.3%
1 154
 
0.1%

Response Type_Euthanize
Categorical

IMBALANCE  MISSING 

Distinct2
Distinct (%)< 0.1%
Missing1462
Missing (%)2.0%
Memory size1.1 MiB
0.0
71856 
1.0
 
340

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters216588
Distinct characters3
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
0.0 71856
97.6%
1.0 340
 
0.5%
(Missing) 1462
 
2.0%

Length

2023-03-18T21:17:54.369145image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-03-18T21:17:54.460636image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
0.0 71856
99.5%
1.0 340
 
0.5%

Most occurring characters

ValueCountFrequency (%)
0 144052
66.5%
. 72196
33.3%
1 340
 
0.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 144392
66.7%
Other Punctuation 72196
33.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 144052
99.8%
1 340
 
0.2%
Other Punctuation
ValueCountFrequency (%)
. 72196
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 216588
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 144052
66.5%
. 72196
33.3%
1 340
 
0.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 216588
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 144052
66.5%
. 72196
33.3%
1 340
 
0.2%

Response Type_Evacuate Visitor
Categorical

IMBALANCE  MISSING 

Distinct2
Distinct (%)< 0.1%
Missing1462
Missing (%)2.0%
Memory size1.1 MiB
0.0
72074 
1.0
 
122

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters216588
Distinct characters3
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
0.0 72074
97.8%
1.0 122
 
0.2%
(Missing) 1462
 
2.0%

Length

2023-03-18T21:17:54.537853image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-03-18T21:17:54.629313image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
0.0 72074
99.8%
1.0 122
 
0.2%

Most occurring characters

ValueCountFrequency (%)
0 144270
66.6%
. 72196
33.3%
1 122
 
0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 144392
66.7%
Other Punctuation 72196
33.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 144270
99.9%
1 122
 
0.1%
Other Punctuation
ValueCountFrequency (%)
. 72196
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 216588
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 144270
66.6%
. 72196
33.3%
1 122
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 216588
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 144270
66.6%
. 72196
33.3%
1 122
 
0.1%

Response Type_Haze - Hard
Categorical

HIGH CORRELATION  IMBALANCE  MISSING 

Distinct2
Distinct (%)< 0.1%
Missing1462
Missing (%)2.0%
Memory size1.1 MiB
0.0
69432 
1.0
 
2764

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters216588
Distinct characters3
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
0.0 69432
94.3%
1.0 2764
 
3.8%
(Missing) 1462
 
2.0%

Length

2023-03-18T21:17:54.707610image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-03-18T21:17:54.799511image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
0.0 69432
96.2%
1.0 2764
 
3.8%

Most occurring characters

ValueCountFrequency (%)
0 141628
65.4%
. 72196
33.3%
1 2764
 
1.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 144392
66.7%
Other Punctuation 72196
33.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 141628
98.1%
1 2764
 
1.9%
Other Punctuation
ValueCountFrequency (%)
. 72196
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 216588
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 141628
65.4%
. 72196
33.3%
1 2764
 
1.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 216588
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 141628
65.4%
. 72196
33.3%
1 2764
 
1.3%

Response Type_Haze - Soft
Categorical

HIGH CORRELATION  MISSING 

Distinct2
Distinct (%)< 0.1%
Missing1462
Missing (%)2.0%
Memory size1.1 MiB
0.0
47726 
1.0
24470 

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters216588
Distinct characters3
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
0.0 47726
64.8%
1.0 24470
33.2%
(Missing) 1462
 
2.0%

Length

2023-03-18T21:17:54.878053image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-03-18T21:17:54.971477image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
0.0 47726
66.1%
1.0 24470
33.9%

Most occurring characters

ValueCountFrequency (%)
0 119922
55.4%
. 72196
33.3%
1 24470
 
11.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 144392
66.7%
Other Punctuation 72196
33.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 119922
83.1%
1 24470
 
16.9%
Other Punctuation
ValueCountFrequency (%)
. 72196
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 216588
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 119922
55.4%
. 72196
33.3%
1 24470
 
11.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 216588
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 119922
55.4%
. 72196
33.3%
1 24470
 
11.3%

Response Type_Immobilize Animal
Categorical

IMBALANCE  MISSING 

Distinct2
Distinct (%)< 0.1%
Missing1462
Missing (%)2.0%
Memory size1.1 MiB
0.0
72083 
1.0
 
113

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters216588
Distinct characters3
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
0.0 72083
97.9%
1.0 113
 
0.2%
(Missing) 1462
 
2.0%

Length

2023-03-18T21:17:55.052448image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-03-18T21:17:55.145366image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
0.0 72083
99.8%
1.0 113
 
0.2%

Most occurring characters

ValueCountFrequency (%)
0 144279
66.6%
. 72196
33.3%
1 113
 
0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 144392
66.7%
Other Punctuation 72196
33.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 144279
99.9%
1 113
 
0.1%
Other Punctuation
ValueCountFrequency (%)
. 72196
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 216588
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 144279
66.6%
. 72196
33.3%
1 113
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 216588
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 144279
66.6%
. 72196
33.3%
1 113
 
0.1%

Response Type_Inform Visitor
Categorical

IMBALANCE  MISSING 

Distinct2
Distinct (%)< 0.1%
Missing1462
Missing (%)2.0%
Memory size1.1 MiB
0.0
69144 
1.0
 
3052

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters216588
Distinct characters3
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
0.0 69144
93.9%
1.0 3052
 
4.1%
(Missing) 1462
 
2.0%

Length

2023-03-18T21:17:55.223612image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-03-18T21:17:55.315667image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
0.0 69144
95.8%
1.0 3052
 
4.2%

Most occurring characters

ValueCountFrequency (%)
0 141340
65.3%
. 72196
33.3%
1 3052
 
1.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 144392
66.7%
Other Punctuation 72196
33.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 141340
97.9%
1 3052
 
2.1%
Other Punctuation
ValueCountFrequency (%)
. 72196
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 216588
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 141340
65.3%
. 72196
33.3%
1 3052
 
1.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 216588
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 141340
65.3%
. 72196
33.3%
1 3052
 
1.4%

Response Type_Infrastructure modification
Categorical

HIGH CORRELATION  IMBALANCE  MISSING 

Distinct2
Distinct (%)< 0.1%
Missing1462
Missing (%)2.0%
Memory size1.1 MiB
0.0
71924 
1.0
 
272

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters216588
Distinct characters3
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
0.0 71924
97.6%
1.0 272
 
0.4%
(Missing) 1462
 
2.0%

Length

2023-03-18T21:17:55.393920image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-03-18T21:17:55.485516image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
0.0 71924
99.6%
1.0 272
 
0.4%

Most occurring characters

ValueCountFrequency (%)
0 144120
66.5%
. 72196
33.3%
1 272
 
0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 144392
66.7%
Other Punctuation 72196
33.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 144120
99.8%
1 272
 
0.2%
Other Punctuation
ValueCountFrequency (%)
. 72196
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 216588
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 144120
66.5%
. 72196
33.3%
1 272
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 216588
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 144120
66.5%
. 72196
33.3%
1 272
 
0.1%
Distinct2
Distinct (%)< 0.1%
Missing1462
Missing (%)2.0%
Memory size1.1 MiB
0.0
52086 
1.0
20110 

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters216588
Distinct characters3
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1.0
2nd row1.0
3rd row1.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
0.0 52086
70.7%
1.0 20110
 
27.3%
(Missing) 1462
 
2.0%

Length

2023-03-18T21:17:55.562627image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-03-18T21:17:55.654927image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
0.0 52086
72.1%
1.0 20110
 
27.9%

Most occurring characters

ValueCountFrequency (%)
0 124282
57.4%
. 72196
33.3%
1 20110
 
9.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 144392
66.7%
Other Punctuation 72196
33.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 124282
86.1%
1 20110
 
13.9%
Other Punctuation
ValueCountFrequency (%)
. 72196
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 216588
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 124282
57.4%
. 72196
33.3%
1 20110
 
9.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 216588
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 124282
57.4%
. 72196
33.3%
1 20110
 
9.3%

Response Type_Issue Prohibited Activity Order
Categorical

HIGH CORRELATION  IMBALANCE  MISSING 

Distinct2
Distinct (%)< 0.1%
Missing1462
Missing (%)2.0%
Memory size1.1 MiB
0.0
72164 
1.0
 
32

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters216588
Distinct characters3
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
0.0 72164
98.0%
1.0 32
 
< 0.1%
(Missing) 1462
 
2.0%

Length

2023-03-18T21:17:55.735542image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-03-18T21:17:55.828056image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
0.0 72164
> 99.9%
1.0 32
 
< 0.1%

Most occurring characters

ValueCountFrequency (%)
0 144360
66.7%
. 72196
33.3%
1 32
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 144392
66.7%
Other Punctuation 72196
33.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 144360
> 99.9%
1 32
 
< 0.1%
Other Punctuation
ValueCountFrequency (%)
. 72196
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 216588
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 144360
66.7%
. 72196
33.3%
1 32
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 216588
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 144360
66.7%
. 72196
33.3%
1 32
 
< 0.1%

Response Type_Issue Restricted Activity Order
Categorical

IMBALANCE  MISSING 

Distinct2
Distinct (%)< 0.1%
Missing1462
Missing (%)2.0%
Memory size1.1 MiB
0.0
72111 
1.0
 
85

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters216588
Distinct characters3
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
0.0 72111
97.9%
1.0 85
 
0.1%
(Missing) 1462
 
2.0%

Length

2023-03-18T21:17:55.905711image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-03-18T21:17:55.997830image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
0.0 72111
99.9%
1.0 85
 
0.1%

Most occurring characters

ValueCountFrequency (%)
0 144307
66.6%
. 72196
33.3%
1 85
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 144392
66.7%
Other Punctuation 72196
33.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 144307
99.9%
1 85
 
0.1%
Other Punctuation
ValueCountFrequency (%)
. 72196
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 216588
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 144307
66.6%
. 72196
33.3%
1 85
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 216588
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 144307
66.6%
. 72196
33.3%
1 85
 
< 0.1%

Response Type_Issue Stop Work Order
Categorical

HIGH CORRELATION  IMBALANCE  MISSING 

Distinct2
Distinct (%)< 0.1%
Missing1462
Missing (%)2.0%
Memory size1.1 MiB
0.0
72193 
1.0
 
3

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters216588
Distinct characters3
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
0.0 72193
98.0%
1.0 3
 
< 0.1%
(Missing) 1462
 
2.0%

Length

2023-03-18T21:17:56.075369image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-03-18T21:17:56.167665image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
0.0 72193
> 99.9%
1.0 3
 
< 0.1%

Most occurring characters

ValueCountFrequency (%)
0 144389
66.7%
. 72196
33.3%
1 3
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 144392
66.7%
Other Punctuation 72196
33.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 144389
> 99.9%
1 3
 
< 0.1%
Other Punctuation
ValueCountFrequency (%)
. 72196
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 216588
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 144389
66.7%
. 72196
33.3%
1 3
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 216588
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 144389
66.7%
. 72196
33.3%
1 3
 
< 0.1%

Response Type_Leave on Landscape
Categorical

IMBALANCE  MISSING 

Distinct2
Distinct (%)< 0.1%
Missing1462
Missing (%)2.0%
Memory size1.1 MiB
0.0
71195 
1.0
 
1001

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters216588
Distinct characters3
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
0.0 71195
96.7%
1.0 1001
 
1.4%
(Missing) 1462
 
2.0%

Length

2023-03-18T21:17:56.247660image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-03-18T21:17:56.339453image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
0.0 71195
98.6%
1.0 1001
 
1.4%

Most occurring characters

ValueCountFrequency (%)
0 143391
66.2%
. 72196
33.3%
1 1001
 
0.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 144392
66.7%
Other Punctuation 72196
33.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 143391
99.3%
1 1001
 
0.7%
Other Punctuation
ValueCountFrequency (%)
. 72196
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 216588
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 143391
66.2%
. 72196
33.3%
1 1001
 
0.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 216588
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 143391
66.2%
. 72196
33.3%
1 1001
 
0.5%

Response Type_Mark - paint
Categorical

IMBALANCE  MISSING 

Distinct2
Distinct (%)< 0.1%
Missing1462
Missing (%)2.0%
Memory size1.1 MiB
0.0
72110 
1.0
 
86

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters216588
Distinct characters3
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
0.0 72110
97.9%
1.0 86
 
0.1%
(Missing) 1462
 
2.0%

Length

2023-03-18T21:17:56.417072image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-03-18T21:17:56.508653image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
0.0 72110
99.9%
1.0 86
 
0.1%

Most occurring characters

ValueCountFrequency (%)
0 144306
66.6%
. 72196
33.3%
1 86
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 144392
66.7%
Other Punctuation 72196
33.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 144306
99.9%
1 86
 
0.1%
Other Punctuation
ValueCountFrequency (%)
. 72196
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 216588
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 144306
66.6%
. 72196
33.3%
1 86
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 216588
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 144306
66.6%
. 72196
33.3%
1 86
 
< 0.1%

Response Type_Monitor - Camera
Categorical

HIGH CORRELATION  IMBALANCE  MISSING 

Distinct2
Distinct (%)< 0.1%
Missing1462
Missing (%)2.0%
Memory size1.1 MiB
0.0
71838 
1.0
 
358

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters216588
Distinct characters3
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
0.0 71838
97.5%
1.0 358
 
0.5%
(Missing) 1462
 
2.0%

Length

2023-03-18T21:17:56.586269image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-03-18T21:17:56.678276image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
0.0 71838
99.5%
1.0 358
 
0.5%

Most occurring characters

ValueCountFrequency (%)
0 144034
66.5%
. 72196
33.3%
1 358
 
0.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 144392
66.7%
Other Punctuation 72196
33.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 144034
99.8%
1 358
 
0.2%
Other Punctuation
ValueCountFrequency (%)
. 72196
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 216588
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 144034
66.5%
. 72196
33.3%
1 358
 
0.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 216588
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 144034
66.5%
. 72196
33.3%
1 358
 
0.2%
Distinct2
Distinct (%)< 0.1%
Missing1462
Missing (%)2.0%
Memory size1.1 MiB
0.0
61565 
1.0
10631 

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters216588
Distinct characters3
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1.0
2nd row1.0
3rd row1.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
0.0 61565
83.6%
1.0 10631
 
14.4%
(Missing) 1462
 
2.0%

Length

2023-03-18T21:17:56.756595image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-03-18T21:17:56.849033image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
0.0 61565
85.3%
1.0 10631
 
14.7%

Most occurring characters

ValueCountFrequency (%)
0 133761
61.8%
. 72196
33.3%
1 10631
 
4.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 144392
66.7%
Other Punctuation 72196
33.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 133761
92.6%
1 10631
 
7.4%
Other Punctuation
ValueCountFrequency (%)
. 72196
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 216588
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 133761
61.8%
. 72196
33.3%
1 10631
 
4.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 216588
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 133761
61.8%
. 72196
33.3%
1 10631
 
4.9%
Distinct2
Distinct (%)< 0.1%
Missing1462
Missing (%)2.0%
Memory size1.1 MiB
0.0
68460 
1.0
 
3736

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters216588
Distinct characters3
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
0.0 68460
92.9%
1.0 3736
 
5.1%
(Missing) 1462
 
2.0%

Length

2023-03-18T21:17:56.928878image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-03-18T21:17:57.150432image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
0.0 68460
94.8%
1.0 3736
 
5.2%

Most occurring characters

ValueCountFrequency (%)
0 140656
64.9%
. 72196
33.3%
1 3736
 
1.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 144392
66.7%
Other Punctuation 72196
33.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 140656
97.4%
1 3736
 
2.6%
Other Punctuation
ValueCountFrequency (%)
. 72196
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 216588
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 140656
64.9%
. 72196
33.3%
1 3736
 
1.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 216588
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 140656
64.9%
. 72196
33.3%
1 3736
 
1.7%

Response Type_Necropsy
Categorical

HIGH CORRELATION  IMBALANCE  MISSING 

Distinct2
Distinct (%)< 0.1%
Missing1462
Missing (%)2.0%
Memory size1.1 MiB
0.0
71779 
1.0
 
417

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters216588
Distinct characters3
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
0.0 71779
97.4%
1.0 417
 
0.6%
(Missing) 1462
 
2.0%

Length

2023-03-18T21:17:57.227576image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-03-18T21:17:57.319173image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
0.0 71779
99.4%
1.0 417
 
0.6%

Most occurring characters

ValueCountFrequency (%)
0 143975
66.5%
. 72196
33.3%
1 417
 
0.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 144392
66.7%
Other Punctuation 72196
33.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 143975
99.7%
1 417
 
0.3%
Other Punctuation
ValueCountFrequency (%)
. 72196
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 216588
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 143975
66.5%
. 72196
33.3%
1 417
 
0.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 216588
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 143975
66.5%
. 72196
33.3%
1 417
 
0.2%

Response Type_No response required
Categorical

IMBALANCE  MISSING 

Distinct2
Distinct (%)< 0.1%
Missing1462
Missing (%)2.0%
Memory size1.1 MiB
0.0
71904 
1.0
 
292

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters216588
Distinct characters3
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
0.0 71904
97.6%
1.0 292
 
0.4%
(Missing) 1462
 
2.0%

Length

2023-03-18T21:17:57.396413image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-03-18T21:17:57.488163image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
0.0 71904
99.6%
1.0 292
 
0.4%

Most occurring characters

ValueCountFrequency (%)
0 144100
66.5%
. 72196
33.3%
1 292
 
0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 144392
66.7%
Other Punctuation 72196
33.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 144100
99.8%
1 292
 
0.2%
Other Punctuation
ValueCountFrequency (%)
. 72196
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 216588
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 144100
66.5%
. 72196
33.3%
1 292
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 216588
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 144100
66.5%
. 72196
33.3%
1 292
 
0.1%

Response Type_Not Applicable
Categorical

IMBALANCE  MISSING 

Distinct2
Distinct (%)< 0.1%
Missing1462
Missing (%)2.0%
Memory size1.1 MiB
0.0
71860 
1.0
 
336

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters216588
Distinct characters3
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
0.0 71860
97.6%
1.0 336
 
0.5%
(Missing) 1462
 
2.0%

Length

2023-03-18T21:17:57.565683image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-03-18T21:17:57.657700image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
0.0 71860
99.5%
1.0 336
 
0.5%

Most occurring characters

ValueCountFrequency (%)
0 144056
66.5%
. 72196
33.3%
1 336
 
0.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 144392
66.7%
Other Punctuation 72196
33.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 144056
99.8%
1 336
 
0.2%
Other Punctuation
ValueCountFrequency (%)
. 72196
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 216588
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 144056
66.5%
. 72196
33.3%
1 336
 
0.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 216588
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 144056
66.5%
. 72196
33.3%
1 336
 
0.2%

Response Type_Refer incident to other agency
Categorical

IMBALANCE  MISSING 

Distinct2
Distinct (%)< 0.1%
Missing1462
Missing (%)2.0%
Memory size1.1 MiB
0.0
71600 
1.0
 
596

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters216588
Distinct characters3
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
0.0 71600
97.2%
1.0 596
 
0.8%
(Missing) 1462
 
2.0%

Length

2023-03-18T21:17:57.736519image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-03-18T21:17:57.829460image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
0.0 71600
99.2%
1.0 596
 
0.8%

Most occurring characters

ValueCountFrequency (%)
0 143796
66.4%
. 72196
33.3%
1 596
 
0.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 144392
66.7%
Other Punctuation 72196
33.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 143796
99.6%
1 596
 
0.4%
Other Punctuation
ValueCountFrequency (%)
. 72196
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 216588
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 143796
66.4%
. 72196
33.3%
1 596
 
0.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 216588
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 143796
66.4%
. 72196
33.3%
1 596
 
0.3%

Response Type_Rehabilitate area
Categorical

IMBALANCE  MISSING 

Distinct2
Distinct (%)< 0.1%
Missing1462
Missing (%)2.0%
Memory size1.1 MiB
0.0
72169 
1.0
 
27

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters216588
Distinct characters3
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
0.0 72169
98.0%
1.0 27
 
< 0.1%
(Missing) 1462
 
2.0%

Length

2023-03-18T21:17:57.908220image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-03-18T21:17:58.001477image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
0.0 72169
> 99.9%
1.0 27
 
< 0.1%

Most occurring characters

ValueCountFrequency (%)
0 144365
66.7%
. 72196
33.3%
1 27
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 144392
66.7%
Other Punctuation 72196
33.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 144365
> 99.9%
1 27
 
< 0.1%
Other Punctuation
ValueCountFrequency (%)
. 72196
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 216588
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 144365
66.7%
. 72196
33.3%
1 27
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 216588
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 144365
66.7%
. 72196
33.3%
1 27
 
< 0.1%

Response Type_Relocate animal (s)
Categorical

IMBALANCE  MISSING 

Distinct2
Distinct (%)< 0.1%
Missing1462
Missing (%)2.0%
Memory size1.1 MiB
0.0
69736 
1.0
 
2460

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters216588
Distinct characters3
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
0.0 69736
94.7%
1.0 2460
 
3.3%
(Missing) 1462
 
2.0%

Length

2023-03-18T21:17:58.080288image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-03-18T21:17:58.172994image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
0.0 69736
96.6%
1.0 2460
 
3.4%

Most occurring characters

ValueCountFrequency (%)
0 141932
65.5%
. 72196
33.3%
1 2460
 
1.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 144392
66.7%
Other Punctuation 72196
33.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 141932
98.3%
1 2460
 
1.7%
Other Punctuation
ValueCountFrequency (%)
. 72196
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 216588
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 141932
65.5%
. 72196
33.3%
1 2460
 
1.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 216588
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 141932
65.5%
. 72196
33.3%
1 2460
 
1.1%

Response Type_Request assistance - other Agency
Categorical

IMBALANCE  MISSING 

Distinct2
Distinct (%)< 0.1%
Missing1462
Missing (%)2.0%
Memory size1.1 MiB
0.0
71923 
1.0
 
273

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters216588
Distinct characters3
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
0.0 71923
97.6%
1.0 273
 
0.4%
(Missing) 1462
 
2.0%

Length

2023-03-18T21:17:58.255616image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-03-18T21:17:58.349384image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
0.0 71923
99.6%
1.0 273
 
0.4%

Most occurring characters

ValueCountFrequency (%)
0 144119
66.5%
. 72196
33.3%
1 273
 
0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 144392
66.7%
Other Punctuation 72196
33.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 144119
99.8%
1 273
 
0.2%
Other Punctuation
ValueCountFrequency (%)
. 72196
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 216588
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 144119
66.5%
. 72196
33.3%
1 273
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 216588
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 144119
66.5%
. 72196
33.3%
1 273
 
0.1%

Response Type_Request assistance - police
Categorical

IMBALANCE  MISSING 

Distinct2
Distinct (%)< 0.1%
Missing1462
Missing (%)2.0%
Memory size1.1 MiB
0.0
71984 
1.0
 
212

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters216588
Distinct characters3
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
0.0 71984
97.7%
1.0 212
 
0.3%
(Missing) 1462
 
2.0%

Length

2023-03-18T21:17:58.428301image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-03-18T21:17:58.521689image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
0.0 71984
99.7%
1.0 212
 
0.3%

Most occurring characters

ValueCountFrequency (%)
0 144180
66.6%
. 72196
33.3%
1 212
 
0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 144392
66.7%
Other Punctuation 72196
33.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 144180
99.9%
1 212
 
0.1%
Other Punctuation
ValueCountFrequency (%)
. 72196
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 216588
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 144180
66.6%
. 72196
33.3%
1 212
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 216588
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 144180
66.6%
. 72196
33.3%
1 212
 
0.1%

Response Type_Traffic control
Categorical

IMBALANCE  MISSING 

Distinct2
Distinct (%)< 0.1%
Missing1462
Missing (%)2.0%
Memory size1.1 MiB
0.0
70015 
1.0
 
2181

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters216588
Distinct characters3
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
0.0 70015
95.1%
1.0 2181
 
3.0%
(Missing) 1462
 
2.0%

Length

2023-03-18T21:17:58.601219image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-03-18T21:17:58.697315image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
0.0 70015
97.0%
1.0 2181
 
3.0%

Most occurring characters

ValueCountFrequency (%)
0 142211
65.7%
. 72196
33.3%
1 2181
 
1.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 144392
66.7%
Other Punctuation 72196
33.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 142211
98.5%
1 2181
 
1.5%
Other Punctuation
ValueCountFrequency (%)
. 72196
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 216588
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 142211
65.7%
. 72196
33.3%
1 2181
 
1.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 216588
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 142211
65.7%
. 72196
33.3%
1 2181
 
1.0%

Response Type_Translocate
Categorical

IMBALANCE  MISSING 

Distinct2
Distinct (%)< 0.1%
Missing1462
Missing (%)2.0%
Memory size1.1 MiB
0.0
72161 
1.0
 
35

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters216588
Distinct characters3
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
0.0 72161
98.0%
1.0 35
 
< 0.1%
(Missing) 1462
 
2.0%

Length

2023-03-18T21:17:58.774981image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-03-18T21:17:58.867087image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
0.0 72161
> 99.9%
1.0 35
 
< 0.1%

Most occurring characters

ValueCountFrequency (%)
0 144357
66.7%
. 72196
33.3%
1 35
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 144392
66.7%
Other Punctuation 72196
33.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 144357
> 99.9%
1 35
 
< 0.1%
Other Punctuation
ValueCountFrequency (%)
. 72196
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 216588
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 144357
66.7%
. 72196
33.3%
1 35
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 216588
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 144357
66.7%
. 72196
33.3%
1 35
 
< 0.1%

Response Type_Trap or snare
Categorical

IMBALANCE  MISSING 

Distinct2
Distinct (%)< 0.1%
Missing1462
Missing (%)2.0%
Memory size1.1 MiB
0.0
70652 
1.0
 
1544

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters216588
Distinct characters3
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
0.0 70652
95.9%
1.0 1544
 
2.1%
(Missing) 1462
 
2.0%

Length

2023-03-18T21:17:58.944320image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-03-18T21:17:59.035897image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
0.0 70652
97.9%
1.0 1544
 
2.1%

Most occurring characters

ValueCountFrequency (%)
0 142848
66.0%
. 72196
33.3%
1 1544
 
0.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 144392
66.7%
Other Punctuation 72196
33.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 142848
98.9%
1 1544
 
1.1%
Other Punctuation
ValueCountFrequency (%)
. 72196
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 216588
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 142848
66.0%
. 72196
33.3%
1 1544
 
0.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 216588
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 142848
66.0%
. 72196
33.3%
1 1544
 
0.7%

Response Type_Unable to respond
Categorical

IMBALANCE  MISSING 

Distinct2
Distinct (%)< 0.1%
Missing1462
Missing (%)2.0%
Memory size1.1 MiB
0.0
71652 
1.0
 
544

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters216588
Distinct characters3
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
0.0 71652
97.3%
1.0 544
 
0.7%
(Missing) 1462
 
2.0%

Length

2023-03-18T21:17:59.113209image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-03-18T21:17:59.204599image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
0.0 71652
99.2%
1.0 544
 
0.8%

Most occurring characters

ValueCountFrequency (%)
0 143848
66.4%
. 72196
33.3%
1 544
 
0.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 144392
66.7%
Other Punctuation 72196
33.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 143848
99.6%
1 544
 
0.4%
Other Punctuation
ValueCountFrequency (%)
. 72196
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 216588
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 143848
66.4%
. 72196
33.3%
1 544
 
0.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 216588
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 143848
66.4%
. 72196
33.3%
1 544
 
0.3%

Response Type_Warning signs
Categorical

IMBALANCE  MISSING 

Distinct2
Distinct (%)< 0.1%
Missing1462
Missing (%)2.0%
Memory size1.1 MiB
0.0
70716 
1.0
 
1480

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters216588
Distinct characters3
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
0.0 70716
96.0%
1.0 1480
 
2.0%
(Missing) 1462
 
2.0%

Length

2023-03-18T21:17:59.281635image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-03-18T21:17:59.373077image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
0.0 70716
98.0%
1.0 1480
 
2.0%

Most occurring characters

ValueCountFrequency (%)
0 142912
66.0%
. 72196
33.3%
1 1480
 
0.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 144392
66.7%
Other Punctuation 72196
33.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 142912
99.0%
1 1480
 
1.0%
Other Punctuation
ValueCountFrequency (%)
. 72196
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 216588
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 142912
66.0%
. 72196
33.3%
1 1480
 
0.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 216588
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 142912
66.0%
. 72196
33.3%
1 1480
 
0.7%

Response Type_nan
Categorical

HIGH CORRELATION  IMBALANCE  MISSING 

Distinct2
Distinct (%)< 0.1%
Missing1462
Missing (%)2.0%
Memory size1.1 MiB
0.0
69726 
1.0
 
2470

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters216588
Distinct characters3
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
0.0 69726
94.7%
1.0 2470
 
3.4%
(Missing) 1462
 
2.0%

Length

2023-03-18T21:17:59.450197image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-03-18T21:17:59.541608image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
0.0 69726
96.6%
1.0 2470
 
3.4%

Most occurring characters

ValueCountFrequency (%)
0 141922
65.5%
. 72196
33.3%
1 2470
 
1.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 144392
66.7%
Other Punctuation 72196
33.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 141922
98.3%
1 2470
 
1.7%
Other Punctuation
ValueCountFrequency (%)
. 72196
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 216588
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 141922
65.5%
. 72196
33.3%
1 2470
 
1.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 216588
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 141922
65.5%
. 72196
33.3%
1 2470
 
1.1%

Interactions

2023-03-18T21:17:07.625569image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-03-18T21:17:05.103981image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-03-18T21:17:05.717839image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-03-18T21:17:06.284650image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-03-18T21:17:06.862541image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-03-18T21:17:07.746095image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-03-18T21:17:05.249546image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-03-18T21:17:05.831510image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-03-18T21:17:06.402946image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-03-18T21:17:06.977468image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-03-18T21:17:07.862163image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-03-18T21:17:05.361748image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-03-18T21:17:05.939607image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-03-18T21:17:06.512187image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-03-18T21:17:07.087581image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-03-18T21:17:07.980022image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-03-18T21:17:05.479901image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-03-18T21:17:06.054805image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-03-18T21:17:06.627076image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-03-18T21:17:07.204533image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-03-18T21:17:08.095246image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-03-18T21:17:05.593914image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-03-18T21:17:06.164864image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-03-18T21:17:06.740175image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-03-18T21:17:07.314417image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Correlations

2023-03-18T21:17:59.950925image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Latitude PublicLongitude PublicTotal Staff InvolvedTotal Staff HoursSum of Number of AnimalsField UnitProtected Heritage AreaIncident TypeWithin ParkAnimal Health StatusCause of Animal Health StatusAnimal BehaviourReason for Animal BehaviourAnimal AttractantDeterrents UsedAnimal Response to DeterrentsActivity Type_Backpacking – Multiday TripsActivity Type_Beach RecreationActivity Type_Boating - Coastal/MarineActivity Type_Boating - CommercialActivity Type_Boating - Motorized Pleasure CraftActivity Type_Bush PartyActivity Type_Camping - BackcountryActivity Type_Camping - FrontcountryActivity Type_Camping - Huts and LodgesActivity Type_Camping - Winter FrontcountryActivity Type_Canoeing - FlatwaterActivity Type_Canoeing - SwiftwaterActivity Type_CanyoneeringActivity Type_Climbing - MountaineeringActivity Type_Climbing - Technical RockActivity Type_Climbing - Waterfall IceActivity Type_Commercial Transportation OperationActivity Type_CyclingActivity Type_Cycling - Mountain BikingActivity Type_Cycling - Road/Shared PathActivity Type_Cycling - WinterActivity Type_Dog WalkingActivity Type_DogsleddingActivity Type_Domestic Residence ActivityActivity Type_DrivingActivity Type_Field SportsActivity Type_FishingActivity Type_Flight - HETSActivity Type_Flight - Hang-gliding/ParapentingActivity Type_Flight - HelicopterActivity Type_Flight - Sightseeing/Site AccessActivity Type_GolfingActivity Type_Heritage Activity - Bird WatchingActivity Type_Heritage Activity - History ActivitiesActivity Type_Heritage Activity - Photography and ArtActivity Type_Heritage Activity - SightseeingActivity Type_Heritage Activity - Wildlife ObservationActivity Type_Hiking / WalkingActivity Type_Horse Riding - Day TripActivity Type_Horse Riding - MultidayActivity Type_Ice SkatingActivity Type_Kayaking - CoastalActivity Type_Kayaking - FlatwaterActivity Type_Kayaking - SwiftwaterActivity Type_MooringActivity Type_Not ApplicableActivity Type_Orienteering / GeocachingActivity Type_OtherActivity Type_Paddleboarding - CoastalActivity Type_Paddleboarding - FlatwaterActivity Type_Park OperationsActivity Type_Park Ops - Avalanche ForecastingActivity Type_Park Ops - Avalanche ControlActivity Type_Park Ops - Search and RescueActivity Type_Park Ops - TrainingActivity Type_Picnicking / BBQActivity Type_Playground ActivitiesActivity Type_Rafting - FlatwaterActivity Type_Rafting - SwiftwaterActivity Type_RailwayActivity Type_Research - Scientific/SocialActivity Type_Resource Harvesting - Hunting/Fishing/Gathering/TrappingActivity Type_Roller SportsActivity Type_Running - RoadActivity Type_Running - TrailActivity Type_Sail Sports - Wind / Kite SurfingActivity Type_ScramblingActivity Type_Skiing - CrosscountryActivity Type_Skiing/Boarding - BackcountryActivity Type_Skiing/Boarding - Ski Resort In BoundsActivity Type_Skiing/Boarding - Ski Resort Out of BoundsActivity Type_Sledding/TobogganningActivity Type_SnowmobilingActivity Type_SnowshoeingActivity Type_Special Event - Participative AudienceActivity Type_Special Events - Passive AudienceActivity Type_Stakeholder OperationsActivity Type_SurfingActivity Type_Swimming - Cliff JumpingActivity Type_Swimming - CoastalActivity Type_Swimming - FacilitiesActivity Type_Swimming - Flat WaterActivity Type_Swimming - SwiftwaterActivity Type_Townsite ActivityActivity Type_Tram/Ski Lift/GondolaActivity Type_Tubing / River DriftingActivity Type_UnknownActivity Type_Via-FerrataActivity Type_nanResponse Type_Response Type_Assist VisitorResponse Type_Assist other AgencyResponse Type_Assist other Field UnitResponse Type_Attractant ManagementResponse Type_Aversive ConditioningResponse Type_Capture and transport to captivityResponse Type_Clean UpResponse Type_Close AreaResponse Type_Close RoadResponse Type_CollarResponse Type_Collect SampleResponse Type_CullResponse Type_Destroy AnimalResponse Type_DisentangleResponse Type_Dispatch other AgencyResponse Type_Disperse Wildlife JamResponse Type_Dispose CarcassResponse Type_Ear TagResponse Type_EuthanizeResponse Type_Evacuate VisitorResponse Type_Haze - HardResponse Type_Haze - SoftResponse Type_Immobilize AnimalResponse Type_Inform VisitorResponse Type_Infrastructure modificationResponse Type_Investigate IncidentResponse Type_Issue Prohibited Activity OrderResponse Type_Issue Restricted Activity OrderResponse Type_Issue Stop Work OrderResponse Type_Leave on LandscapeResponse Type_Mark - paintResponse Type_Monitor - CameraResponse Type_Monitor - patrolResponse Type_Monitor - visitor and staff sightingResponse Type_NecropsyResponse Type_No response requiredResponse Type_Not ApplicableResponse Type_Refer incident to other agencyResponse Type_Rehabilitate areaResponse Type_Relocate animal (s)Response Type_Request assistance - other AgencyResponse Type_Request assistance - policeResponse Type_Traffic controlResponse Type_TranslocateResponse Type_Trap or snareResponse Type_Unable to respondResponse Type_Warning signsResponse Type_nan
Latitude Public1.000-0.4480.0470.026-0.0120.7090.9520.1030.2200.1070.3220.2240.1940.2140.1850.0590.0720.1740.0190.0000.0990.0000.1970.0550.2210.0000.0270.3230.0000.0000.0000.0000.0400.0200.0110.0420.0000.0130.0000.0480.0930.0230.0810.0000.0000.0000.0000.0910.0130.0900.0230.0190.0230.1040.0100.0000.0000.0120.0000.1760.0000.0630.0000.0900.0320.0000.1040.0000.0000.0210.0000.0210.0000.0000.0000.1280.0410.1280.0000.0000.0000.0000.0000.0100.0020.0050.0000.0000.0000.0000.0120.0130.1300.0000.0000.0320.0000.0000.0000.0890.0000.0000.0570.0000.2140.0000.0370.0300.0000.0670.0200.0380.1480.1530.3450.0000.1960.3610.0340.0140.0130.0510.0630.0000.0310.0200.0590.1340.0110.1510.0710.0530.0000.0200.0000.0820.0000.2580.1760.1030.2510.0370.0930.0220.0230.3140.0330.0370.0760.0060.2970.0560.1800.061
Longitude Public-0.4481.000-0.0020.0230.0410.8600.9830.1570.3690.1370.2110.1700.1760.1860.2060.1090.3660.2280.0790.0320.3510.0000.2250.0880.1840.0080.0080.0110.0000.0000.0000.0000.0160.0250.0120.0000.0000.0360.0000.0560.1100.0090.0730.0000.0000.0000.0000.0600.0190.1810.0110.0470.0600.1520.0060.0000.0000.0500.0080.1760.0260.0220.0000.1110.0260.0000.1760.0000.0000.0160.0190.0520.0000.0000.0000.1040.0470.0470.0000.0000.0000.0000.0000.0180.0020.0070.0000.0000.0260.0130.0080.0330.0960.0420.0000.0260.0000.0180.0350.1370.0000.0110.1260.0000.1630.0720.0690.1120.0000.0710.0700.0370.1670.1460.3340.0000.2040.3490.1160.0460.0370.0490.1240.0660.0440.0330.0640.2090.0330.1960.1860.0340.0000.0000.0000.0910.0580.2450.1450.4610.2380.0660.1050.0920.1430.3070.0500.0460.0410.0140.2720.0350.1670.064
Total Staff Involved0.047-0.0021.0000.557-0.0160.0500.1440.0470.0000.0260.0900.0670.0930.0770.0660.0230.0130.0000.0000.0000.0000.0000.0820.0260.0000.0000.0360.0000.0000.0000.0000.0260.0000.0280.0430.0000.0000.0320.0000.0000.0660.0000.0280.0000.0000.0000.0000.0000.0000.0020.0090.0000.0000.0500.0140.0160.0000.0000.0000.0070.0000.0000.0000.0000.0000.0000.0650.0000.0000.0000.0000.0020.0000.0000.0000.0000.0290.0000.0000.0000.0150.0000.0000.0000.0230.0080.0000.0260.0000.0000.0000.0000.0150.0700.0000.0000.0000.0000.0000.0150.0000.0000.0000.0000.0140.0670.0300.0130.0130.1110.0840.0180.0000.2170.0000.0510.0000.0000.0590.0170.0070.0180.0370.0300.0440.0720.0200.0280.1200.0500.0740.0270.0300.0560.0000.0220.0080.1200.0550.0280.0240.0070.0390.0000.0200.1010.0180.0760.0220.0000.0610.0140.1350.062
Total Staff Hours0.0260.0230.5571.000-0.0250.0520.1880.0040.0000.0000.0390.0000.0280.0620.0180.0000.0000.0000.0000.0000.0000.0000.0820.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0080.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0270.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0100.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0130.0000.0000.0000.0000.0170.0000.0000.0000.0000.1100.0820.0000.0000.0690.0000.0000.0000.0000.0000.0000.0000.0000.0300.0000.0000.0000.0170.0100.0000.0390.0000.0140.0000.0000.0000.0000.0000.1180.0210.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0180.0000.0570.033
Sum of Number of Animals-0.0120.041-0.016-0.0251.0000.0410.0410.0120.0000.0000.0000.0000.0000.0330.0001.0000.0000.0160.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0070.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0240.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0310.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0220.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0060.0000.0040.0000.0000.0000.0410.0000.0000.0110.0000.0000.0000.0000.0110.0000.0000.0000.0000.0000.0000.0000.0000.0160.018
Field Unit0.7090.8600.0500.0520.0411.0000.9810.2050.3660.2040.2480.2160.2240.2220.2330.1400.3670.3130.0780.0310.1180.0000.2430.1130.2410.0190.0360.0770.0000.0000.0000.0000.0500.0410.0180.0500.0000.0610.0000.0760.3170.0430.0780.0000.0190.0260.0270.1150.0510.1880.0680.0580.1000.2170.0220.0000.0000.0560.0130.1500.0380.0800.0000.1260.0490.0000.2730.0130.0370.0330.0180.0890.0060.0000.0000.1620.0680.1450.0000.0000.0310.0110.0000.0310.0960.0320.0000.0000.0380.0290.0510.0400.1590.0410.0000.0490.0000.0260.0520.2330.0000.0220.0880.0000.3780.0730.0890.1180.0150.0750.0770.0860.3220.3090.7110.0170.4230.7440.1350.0600.0320.2300.1600.0810.0600.0500.0840.2680.0630.2660.3190.1300.0330.0340.0060.2060.0760.5250.2320.4750.5050.1110.1270.0960.1000.3380.0560.0570.1840.0210.3120.0600.2910.104
Protected Heritage Area0.9520.9830.1440.1880.0410.9811.0000.2160.3960.2050.2550.2040.2330.2270.2020.1350.3670.3140.0790.0270.3630.0000.2660.1470.2650.0300.0370.3250.0000.0000.0000.0000.0480.0400.0160.0490.0000.0580.0000.1070.2480.0340.0860.0000.0120.0300.0270.1090.0480.2130.0670.0580.1250.2290.0160.0000.0000.0560.0000.1700.0350.0820.0000.1320.0470.0000.3010.0120.0440.0300.0120.0900.0050.0000.0000.1690.0850.2150.0000.0000.0470.0140.0000.0270.1580.0100.0000.0000.0350.0220.0540.0410.1590.0380.0000.0470.0060.1470.0500.2160.0000.0340.1400.0000.3380.0720.0960.1220.0080.1020.0840.0860.3290.3090.7110.0380.4230.7440.1490.1180.0560.1190.1850.0980.0610.0550.0860.2480.0660.2720.4280.1330.0270.0380.0000.2150.0750.5270.2370.4760.5060.1320.1700.0950.1420.3860.0640.0590.1180.0180.3630.0470.3090.112
Incident Type0.1030.1570.0470.0040.0120.2050.2161.0000.0650.2860.3120.1990.1960.2290.2380.1480.1180.0730.0280.0060.0400.0250.0450.1010.0290.0120.0210.0090.0110.0000.0000.0300.0780.0160.0150.0260.0000.0820.0000.0530.1530.0170.0000.0250.0450.0310.0030.0750.0350.0160.0910.0220.1310.1350.0190.0320.0000.0130.0300.0000.0000.0140.0000.0600.0000.0140.1660.0230.0170.0000.0120.0640.0140.0250.0110.1230.0310.0350.0000.0150.0150.0000.0230.0290.0980.0270.0000.0100.0000.0090.0040.0000.1260.0030.0000.0000.0100.0140.0000.1620.0460.0200.0480.0120.1510.0150.0400.0770.0230.2300.0250.0890.3450.3240.2990.0470.1940.3050.1580.0670.0940.1220.4730.0130.1190.0230.1250.4020.0380.1850.3740.1790.0880.1030.0000.2170.0210.2290.1690.3100.2110.0290.0480.1570.0560.1680.1300.0940.0920.1470.3410.0470.2530.103
Within Park0.2200.3690.0000.0000.0000.3660.3960.0651.0000.0860.1340.1800.1510.1560.1260.0730.0000.0080.0480.0000.0170.0000.0150.0120.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0230.0000.1330.0150.0000.0190.0000.0000.0000.0070.0130.0000.0450.0010.0010.0050.0000.0000.0000.0000.0430.0000.0000.0000.0060.0000.0570.0160.0000.0030.0000.0000.0000.0000.0030.0000.0000.0000.0110.0000.0770.0040.0150.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0100.0000.0000.0000.0000.0000.0030.0260.0000.0000.0440.0000.0070.0000.0110.2050.0030.0050.0000.0120.0000.0000.0020.0000.0120.0000.0200.0000.0790.0180.0030.0040.0150.0000.0180.0640.0140.0090.0040.0210.0000.0050.0000.0230.0000.0000.0000.0340.0120.0060.0280.1600.0080.0000.0480.0210.0110.0000.0050.0050.0130.017
Animal Health Status0.1070.1370.0260.0000.0000.2040.2050.2860.0861.0000.3030.2210.2220.1920.3300.2620.1920.0930.0350.0480.0270.0000.0920.1120.0390.0000.0090.0361.0000.0000.0000.0000.0870.0000.0190.0280.0000.0210.0000.0360.2090.0110.0130.0000.0000.0000.0000.0450.0320.0000.0110.0230.0350.0560.0190.0000.0000.0300.0000.0150.0000.0080.0000.0781.0000.0000.0910.0000.0070.0000.0140.0330.0000.0000.0150.1270.0290.0320.0100.0000.0000.0000.0000.0200.0000.0000.0000.0000.0240.0000.0000.0000.0580.0131.0000.0240.0000.0000.0090.1650.0000.0240.0550.0220.2660.0000.0080.0930.0050.0500.0180.0860.1860.0930.1370.0060.2340.1380.2290.0530.0360.1110.6560.0300.1790.0370.1050.4680.0360.0430.0000.3180.0000.0031.0000.2780.0130.1060.1760.2810.1940.0150.0380.0650.0190.1110.0600.0290.0670.0270.0580.0300.0630.126
Cause of Animal Health Status0.3220.2110.0900.0390.0000.2480.2550.3120.1340.3031.0000.2030.2590.2550.2850.1380.0960.1950.0220.0570.0830.0430.1460.1850.3050.0000.0620.0561.0000.0571.0001.0000.0920.0000.0130.0491.0000.1471.0000.2020.5930.0000.1021.0001.0000.0230.0250.1000.0750.0390.0390.0800.1720.2920.0400.0280.0000.0000.0100.0570.0000.0001.0000.1031.0000.0000.3740.0310.0000.0000.0450.0850.0000.0000.0640.3080.0570.3891.0000.0000.0360.0001.0000.0950.0160.0470.0000.0150.0430.0000.0000.0000.1930.0161.0000.0000.0390.0000.0000.2670.0000.0000.0770.1250.3271.0000.0660.0330.0000.0440.1310.0190.3670.4860.5970.0420.3400.6130.4320.1620.0250.0680.4430.0550.1250.0600.0850.2780.0740.3990.0260.1820.0000.0001.0000.1610.0000.5700.1740.2030.4790.0000.0670.0850.0000.1950.0000.0940.1030.0440.3180.0000.4830.066
Animal Behaviour0.2240.1700.0670.0000.0000.2160.2040.1990.1800.2210.2031.0000.3740.2640.1550.1850.1320.1650.0260.0190.0581.0000.1930.1580.0800.0260.0200.1950.0000.0000.0000.0720.0310.0720.1020.0730.0190.2800.0620.1180.3180.0420.0440.0300.0100.0000.0000.1270.0380.0000.0400.0140.0630.2360.0650.0360.0000.0270.0160.0290.0330.0500.0000.0711.0000.0190.0921.0000.0000.0000.0150.1170.0220.0000.0000.1790.0690.0750.0550.0390.0901.0001.0000.0660.0170.0350.0620.0290.0110.0340.0490.0000.1480.0690.0000.0380.0000.0300.0000.1750.0000.0520.0830.0000.1940.0380.0950.1150.0200.1230.0400.0380.1650.1150.0000.0270.1590.0960.1060.1080.0370.1560.3060.0920.1570.0750.1150.2560.0450.1420.0550.1750.0220.0420.0000.2760.0990.0930.2100.1550.0960.0510.0640.0930.0230.2070.0680.0690.1020.0220.1510.0710.1720.063
Reason for Animal Behaviour0.1940.1760.0930.0280.0000.2240.2330.1960.1510.2220.2590.3741.0000.3640.1840.1670.1850.1780.0190.0200.0431.0000.1470.1270.1410.0000.0410.0470.0250.0000.0000.0000.0320.0810.1290.0380.0190.3920.0000.1180.1810.0550.0710.0160.0310.0000.0000.0720.0800.0000.0800.0240.1160.2250.0540.0150.0000.0000.0280.1130.0130.0431.0000.0431.0000.0190.0821.0000.0000.0000.0000.1380.0001.0000.0130.0770.0510.0700.0000.0340.1011.0001.0000.0350.0000.0170.0250.0260.0400.1020.0250.0270.1110.0100.0000.0000.0070.0170.0000.1300.0140.0000.0620.0160.1950.0240.0730.0870.0440.1590.0490.0460.1990.1440.0000.0250.1340.0120.1470.0640.0630.1280.2470.0680.2130.0690.1320.3620.0360.0800.0500.1880.0000.0251.0000.2320.0820.0900.0780.2090.1440.0910.0690.0950.0000.3930.0480.0600.1010.0620.1640.0300.1260.077
Animal Attractant0.2140.1860.0770.0620.0330.2220.2270.2290.1560.1920.2550.2640.3641.0000.1800.1850.0910.2160.0310.0000.0580.0000.2270.2200.1160.0000.0400.0451.0000.0000.0001.0000.0840.0150.0220.0420.0230.5130.0260.1630.3600.0910.2061.0000.0000.0000.0170.2620.0560.0110.0700.0400.0790.1720.0460.0000.0000.0040.0370.0000.0120.0450.0000.0551.0000.0390.1530.0420.0120.0000.0000.1850.0001.0000.0120.6300.0690.0720.0000.0280.0221.0001.0000.0870.0000.0520.0000.0271.0000.0240.0300.0000.1150.0001.0001.0000.0220.0000.0000.2750.0241.0000.0461.0000.3070.0330.0440.0650.0000.1600.0250.0000.2320.1880.0000.0000.0990.0000.0980.0300.1360.2210.3380.0960.0900.0400.1220.4080.0310.1260.0670.2510.0240.0000.0000.2020.0310.0880.1120.1210.0930.1120.0670.1590.0000.1950.1390.0790.1680.0330.1810.0360.1600.120
Deterrents Used0.1850.2060.0660.0180.0000.2330.2020.2380.1260.3300.2850.1550.1840.1801.0000.4170.1900.1390.0160.0000.1181.0000.1720.0710.1680.0000.0080.0251.0000.0000.0001.0000.0730.0250.0550.0511.0000.0720.0000.0710.2810.0580.0451.0001.0000.0000.0000.0790.0300.0000.0470.0350.0560.1780.0110.0000.0000.0470.0001.0000.0000.0281.0000.0581.0000.0000.1790.0380.0000.0000.0000.0480.0160.0000.0000.2790.0620.0570.0000.0000.0171.0001.0000.0340.0000.0001.0000.0001.0000.0550.0000.0000.0590.0000.0001.0000.0830.0000.0240.3150.0001.0000.0521.0000.4501.0000.0300.0660.0000.0450.1390.0160.1280.0920.2250.0000.1860.3110.7490.0900.0250.1640.3960.0950.4860.0460.5100.6380.0750.1140.0000.2980.0000.0001.0000.1820.3250.1440.2390.2380.3250.0990.0480.0660.0520.1450.0250.0420.1060.0000.1100.0690.1670.161
Animal Response to Deterrents0.0590.1090.0230.0001.0000.1400.1350.1480.0730.2620.1380.1850.1670.1850.4171.0000.1660.0770.0001.0001.0001.0000.2120.0360.0540.0000.0140.0001.0001.0000.0361.0000.0310.0000.0590.0331.0000.0380.0380.0160.0650.0570.0001.0001.0000.0000.0000.0160.1520.0000.0270.0150.0290.1450.0280.0000.0000.0000.0141.0000.0001.0001.0000.0521.0000.0000.0800.0000.0000.0000.0200.0100.0000.0000.0000.0430.0700.0170.0000.0510.0861.0001.0000.0290.0000.0481.0000.0001.0001.0000.0000.0000.0561.0000.0001.0000.0000.0061.0000.1510.0001.0000.0621.0001.0001.0000.0590.0610.0160.0520.0080.0000.1490.0910.0000.0460.0931.0000.0610.0000.0450.0650.1830.0710.1190.1150.1960.5920.0390.1051.0000.4031.0000.0471.0000.1470.0280.0360.2300.2650.0160.0300.0270.0760.0000.1640.0850.0670.0270.0000.0520.0740.1391.000
Activity Type_Backpacking – Multiday Trips0.0720.3660.0130.0000.0000.3670.3670.1180.0000.1920.0960.1320.1850.0910.1900.1661.0000.0000.0090.0000.0000.0000.1790.0230.0020.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0030.0000.0060.0000.0050.0600.0000.0000.0000.0000.0000.0000.0110.0000.0000.0000.0040.0070.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0040.0000.0000.0140.0000.0000.0000.0000.0050.0000.0000.0000.0170.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0170.0000.0000.0000.0000.0000.0000.0390.0000.0000.0000.0000.0250.0000.0000.0020.0000.0040.0000.0000.0040.0030.0000.0000.0060.0000.0070.0000.0000.0170.0220.0000.0030.0000.0140.0510.0000.0110.0010.0050.0000.0000.0000.0030.0000.0000.0120.2810.0000.0000.0040.0000.0000.0150.0010.0000.0140.0000.0110.0020.0150.012
Activity Type_Beach Recreation0.1740.2280.0000.0000.0160.3130.3140.0730.0080.0930.1950.1650.1780.2160.1390.0770.0001.0000.0000.0020.0040.0000.0040.0200.0030.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0040.0000.0080.0000.0060.0660.0000.0000.0000.0000.0000.0000.0130.0000.0000.0000.0050.0080.0100.0000.0000.0000.0000.0000.0000.0000.0000.0000.0020.0000.0000.0180.0000.0000.0000.0000.0000.0000.0000.0000.0190.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0180.0220.0000.0190.0030.0000.0000.0420.0000.0000.0000.0000.0280.0000.0160.0100.0040.0180.0000.0190.0000.0000.0000.0000.0130.0000.0040.0000.0070.0180.0160.0000.0160.0160.0090.0430.0000.0460.0030.0090.0000.0000.0000.0270.0000.0000.0250.0780.0350.0000.0000.0540.0090.0000.0150.0060.0080.0000.0090.0040.0120.000
Activity Type_Boating - Coastal/Marine0.0190.0790.0000.0000.0000.0780.0790.0280.0480.0350.0220.0260.0190.0310.0160.0000.0090.0001.0000.0000.0000.0000.0000.0030.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0140.0000.0110.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0030.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0080.0000.0000.0000.0000.0040.0000.0020.0920.0000.0000.0000.0090.0000.0000.0000.0000.0000.0000.0000.0000.0050.0000.0000.0000.0000.0000.0000.0100.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0200.0110.0000.0000.0230.0000.0000.0010.0030.0000.0000.0000.0000.0000.003
Activity Type_Boating - Commercial0.0000.0320.0000.0000.0000.0310.0270.0060.0000.0480.0570.0190.0200.0000.0001.0000.0000.0020.0001.0000.0180.0000.0000.0000.0000.0000.0000.0350.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0080.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0030.0000.0000.0000.0000.0000.0000.0080.0000.0000.0000.0000.0180.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0040.0000.0000.0000.0000.0000.0000.0000.0120.0000.0000.0000.0030.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0040.0000.000
Activity Type_Boating - Motorized Pleasure Craft0.0990.3510.0000.0000.0000.1180.3630.0400.0170.0270.0830.0580.0430.0580.1181.0000.0000.0040.0000.0181.0000.0000.0240.0060.0000.0000.0090.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0180.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0060.0000.0000.0000.0190.0000.0000.0000.0000.0000.0000.0000.0000.0040.0000.0000.0000.0000.0000.0000.0000.0000.0030.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0030.0000.0000.0000.0000.0000.0000.0120.0000.0000.0140.0000.0070.0000.0000.0100.0000.0370.0280.0000.0000.0070.0000.0000.0240.0000.0300.0030.0030.0020.0000.0000.0000.0000.0010.0180.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0100.0060.0290.0000.0000.0050.0130.0000.0000.0000.0000.0000.0160.0000.0240.000
Activity Type_Bush Party0.0000.0000.0000.0000.0000.0000.0000.0250.0000.0000.0431.0001.0000.0001.0001.0000.0000.0000.0000.0000.0001.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0140.0000.0000.0000.0000.0000.0000.0000.0000.0000.000
Activity Type_Camping - Backcountry0.1970.2250.0820.0820.0000.2430.2660.0450.0150.0920.1460.1930.1470.2270.1720.2120.1790.0040.0000.0000.0240.0001.0000.0280.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0020.0050.0000.0080.0000.0070.0740.0000.0000.0000.0000.0000.0000.0140.0000.0000.0000.0060.0090.0040.0000.0000.0000.0350.0000.0120.0000.0000.0000.0060.0000.0000.0220.0000.0000.0000.0000.0070.0000.0000.0000.0210.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0210.0000.0000.0000.0000.0000.0000.0470.0000.0000.0000.0000.0310.0000.0180.0080.0000.0340.0000.0000.0000.0440.0010.0000.0010.0000.0000.0000.0000.0210.0160.0000.0050.0210.0190.0620.0000.0430.0030.0400.0000.0060.0000.0070.0000.0470.0000.1240.0000.0040.0200.0060.0000.0170.0000.0000.0170.0000.0070.0000.0750.000
Activity Type_Camping - Frontcountry0.0550.0880.0260.0000.0000.1130.1470.1010.0120.1120.1850.1580.1270.2200.0710.0360.0230.0200.0030.0000.0060.0000.0281.0000.0140.0000.0050.0000.0000.0000.0000.0000.0120.0100.0140.0180.0000.0210.0000.0230.2020.0100.0050.0000.0000.0000.0000.0420.0030.0080.0130.0210.0270.0760.0100.0000.0000.0000.0000.0000.0000.0000.0000.0200.0000.0000.0630.0000.0000.0000.0000.0240.0020.0000.0000.0600.0070.0050.0000.0040.0080.0000.0000.0060.0040.0050.0000.0000.0000.0000.0000.0000.0610.0000.0000.0000.0000.0000.0000.1290.0040.0000.0130.0000.0870.0100.0000.0090.0000.0230.0180.0070.0040.0170.0130.0000.0210.0130.0250.0000.0090.0550.0620.0260.0110.0000.0050.0030.0070.0510.0170.0470.0040.0000.0000.0270.0070.0120.0160.0110.0130.0160.0100.0070.0000.0130.0120.0000.0460.0000.0060.0090.0310.002
Activity Type_Camping - Huts and Lodges0.2210.1840.0000.0000.0000.2410.2650.0290.0000.0390.3050.0800.1410.1160.1680.0540.0020.0030.0000.0000.0000.0000.0000.0141.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0020.0460.0000.0000.0000.0000.0000.0000.0080.0000.0000.0000.0000.0040.0160.0000.0000.0000.0000.0000.0000.0000.0000.0000.0090.0000.0000.0150.0000.0000.0000.0000.0030.0000.0000.0000.0130.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0300.0000.0000.0000.0000.0190.0000.0000.0000.0000.0280.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0100.0120.0000.0000.0000.0000.0290.0000.0080.0000.0110.0000.0000.0000.0060.0000.0120.0080.0030.0000.0070.0090.0000.0000.0970.0000.0000.0070.0000.0000.0020.0090.000
Activity Type_Camping - Winter Frontcountry0.0000.0080.0000.0000.0000.0190.0300.0120.0000.0000.0000.0260.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0001.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0070.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0040.0000.0000.0000.0000.0000.0720.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0020.0000.0000.0000.0000.0000.0130.0000.0000.0000.0040.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0060.0000.0000.000
Activity Type_Canoeing - Flatwater0.0270.0080.0360.0000.0000.0360.0370.0210.0000.0090.0620.0200.0410.0400.0080.0140.0000.0000.0000.0000.0090.0000.0000.0050.0000.0001.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0170.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0570.0000.0000.0000.0000.0000.0000.0000.0030.0000.0000.0000.0000.0000.0000.0000.0000.0010.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0010.0000.0000.0000.0000.0000.0000.0100.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0020.0390.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0150.0000.0030.0000.0040.0000.0000.0000.0290.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0020.0000.0000.0000.0000.0060.000
Activity Type_Canoeing - Swiftwater0.3230.0110.0000.0000.0000.0770.3250.0090.0000.0360.0560.1950.0470.0450.0250.0000.0000.0000.0000.0350.0000.0000.0000.0000.0000.0000.0001.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0090.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0040.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0060.0000.0000.0000.0030.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0140.000
Activity Type_Canyoneering0.0000.0000.0000.0000.0000.0000.0000.0110.0001.0001.0000.0000.0251.0001.0001.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0001.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0620.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0080.000
Activity Type_Climbing - Mountaineering0.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0570.0000.0000.0000.0001.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0001.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0050.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0060.000
Activity Type_Climbing - Technical Rock0.0000.0000.0000.0000.0000.0000.0000.0000.0000.0001.0000.0000.0000.0000.0000.0360.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0001.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0040.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.000
Activity Type_Climbing - Waterfall Ice0.0000.0000.0260.0000.0000.0000.0000.0300.0000.0001.0000.0720.0001.0001.0001.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0001.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0220.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0040.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.000
Activity Type_Commercial Transportation Operation0.0400.0160.0000.0000.0000.0500.0480.0780.0000.0870.0920.0310.0320.0840.0730.0310.0000.0000.0000.0000.0000.0000.0000.0120.0000.0000.0000.0000.0000.0000.0000.0001.0000.0000.0000.0000.0000.0000.0000.0000.0390.0000.0000.0000.0000.0000.0000.0040.0000.0000.0000.0000.0000.0090.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0090.0000.0000.0000.0000.0000.0000.0000.0000.0080.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0060.0000.0000.0000.0000.0000.0000.0200.0000.0000.0000.0000.0120.0000.0000.0000.0000.0190.0000.0000.0340.0000.0000.0000.0000.0000.0000.0000.0220.0060.0930.0000.0310.0000.0070.0310.0000.0080.0000.0130.0000.0000.0000.0000.0000.0070.0090.0060.0000.0000.0000.0140.0000.0070.0000.0000.0060.0000.0040.0000.0000.007
Activity Type_Cycling0.0200.0250.0280.0000.0000.0410.0400.0160.0000.0000.0000.0720.0810.0150.0250.0000.0000.0000.0000.0000.0000.0000.0000.0100.0000.0000.0000.0000.0000.0000.0000.0000.0001.0000.0070.0140.0000.0000.0000.0000.0240.0000.0000.0000.0000.0000.0000.0030.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0080.0000.0000.0000.0000.0000.0000.0000.0000.0070.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0070.0000.0000.0000.0000.0000.0000.0180.0000.0000.0000.0000.0110.0000.0000.0000.0000.0000.0000.0000.0000.0070.0000.0000.0000.0000.0000.0000.0000.0070.0030.0000.0000.0000.0000.0010.0000.0090.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0100.0030.0000.0000.0080.0000.0000.0000.0000.0030.0000.0170.003
Activity Type_Cycling - Mountain Biking0.0110.0120.0430.0000.0000.0180.0160.0150.0000.0190.0130.1020.1290.0220.0550.0590.0000.0000.0000.0000.0000.0000.0020.0140.0000.0000.0000.0000.0000.0000.0000.0000.0000.0071.0000.0050.0000.0000.0000.0000.0360.0000.0000.0000.0000.0000.0000.0060.0000.0000.0000.0000.0010.0020.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0100.0000.0000.0000.0000.0000.0000.0000.0000.0100.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0080.0000.0000.0000.0000.0000.0000.0220.0000.0000.0000.0000.0120.0000.0170.0000.0000.0000.0000.0000.0000.0350.0000.0030.0000.0000.0000.0000.0000.0100.0120.0000.0000.0200.0090.0230.0000.0020.0000.0290.0000.0000.0000.0030.0000.0000.0050.0000.0000.0110.0000.0000.0000.0000.0000.0000.0040.0000.0060.0000.0100.000
Activity Type_Cycling - Road/Shared Path0.0420.0000.0000.0000.0000.0500.0490.0260.0000.0280.0490.0730.0380.0420.0510.0330.0030.0040.0000.0000.0000.0000.0050.0180.0000.0000.0000.0000.0000.0000.0000.0000.0000.0140.0051.0000.0000.0030.0000.0020.0230.0000.0000.0000.0000.0000.0000.0090.0000.0000.0000.0010.0000.0010.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0150.0000.0000.0000.0000.0030.0000.0000.0000.0130.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0120.0000.0000.0000.0000.0000.0000.0300.0000.0000.0000.0000.0200.0000.0070.0000.0000.0010.0000.0000.0060.0030.0000.0000.0000.0000.0000.0000.0000.0020.0130.0000.0000.0030.0000.0100.0030.0040.0000.0100.0000.0050.0000.0000.0000.0000.0260.0000.0010.0000.0000.0000.0000.0080.0000.0000.0000.0000.0070.0000.0000.005
Activity Type_Cycling - Winter0.0000.0000.0000.0000.0000.0000.0000.0000.0000.0001.0000.0190.0190.0231.0001.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0001.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0070.0000.0000.0000.0000.0000.0000.0000.0000.0010.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.000
Activity Type_Dog Walking0.0130.0360.0320.0000.0000.0610.0580.0820.0230.0210.1470.2800.3920.5130.0720.0380.0060.0080.0000.0000.0000.0000.0080.0210.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0030.0001.0000.0000.0050.0630.0000.0000.0000.0000.0000.0000.0100.0000.0000.0000.0000.0000.0050.0000.0000.0000.0000.0000.0000.0000.0000.0000.0050.0000.0000.0220.0000.0000.0000.0000.0040.0000.0000.0000.0180.0000.0000.0000.0000.0080.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0140.0000.0000.0000.0000.0000.0000.0270.0000.0000.0000.0000.0250.0000.0140.0210.0000.0000.0000.0000.0100.0200.0000.0000.0060.0000.0160.0000.0000.0180.0100.0410.0000.0130.0070.0380.0000.0330.0020.0430.0080.0070.0000.0000.0260.0260.0000.0000.0040.0020.0000.0110.0000.0040.0050.0000.0130.0000.0090.0000.0370.002
Activity Type_Dogsledding0.0000.0000.0000.0000.0000.0000.0000.0000.0000.0001.0000.0620.0000.0260.0000.0380.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0001.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0450.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0270.000
Activity Type_Domestic Residence Activity0.0480.0560.0000.0000.0000.0760.1070.0530.1330.0360.2020.1180.1180.1630.0710.0160.0050.0060.0000.0000.0000.0000.0070.0230.0020.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0020.0000.0050.0001.0000.0590.0000.0000.0000.0000.0000.0000.0110.0000.0000.0000.0030.0060.0220.0000.0000.0000.0000.0000.0000.0000.0000.0000.0040.0000.0000.0190.0000.0000.0000.0000.0050.0000.0000.0000.0170.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0160.0000.0000.0000.0000.0000.0000.0380.0000.0000.0000.0000.0250.0000.0000.0450.0000.0000.0000.0120.0080.0080.0000.0000.0050.0000.0000.0000.0000.0160.0050.0050.0000.0000.0080.0390.0070.0200.0000.0120.0000.0000.0000.0080.0000.0020.0000.0160.0030.0000.0140.0270.0000.0520.0170.0020.0120.0180.1350.0040.0000.017
Activity Type_Driving0.0930.1100.0660.0080.0070.3170.2480.1530.0150.2090.5930.3180.1810.3600.2810.0650.0600.0660.0140.0080.0180.0000.0740.2020.0460.0070.0170.0090.0000.0000.0000.0000.0390.0240.0360.0230.0000.0630.0000.0591.0000.0090.0120.0000.0000.0020.0000.1060.0130.0240.0050.0510.0510.1930.0290.0080.0000.0070.0090.0000.0000.0020.0000.0520.0000.0080.1450.0020.0000.0000.0020.0590.0090.0000.0030.1540.0200.0160.0040.0140.0230.0000.0000.0190.0140.0180.0000.0040.0000.0000.0100.0070.1520.0000.0000.0000.0070.0120.0060.3290.0150.0000.0330.0000.2190.0000.0240.0000.0000.0290.0010.0070.0130.0710.0330.0110.0000.0350.0090.0100.0000.2560.1380.0210.0160.0140.0320.0920.0220.0620.0020.0520.0050.0100.0000.0630.0130.0410.0350.0200.0320.0060.0150.0160.0050.1030.0140.0000.1810.0150.1020.0520.0720.034
Activity Type_Field Sports0.0230.0090.0000.0000.0000.0430.0340.0170.0000.0110.0000.0420.0550.0910.0580.0570.0000.0000.0000.0000.0000.0000.0000.0100.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0091.0000.0000.0000.0000.0000.0000.0030.0000.0000.0000.0000.0000.0070.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0080.0000.0000.0000.0000.0000.0000.0000.0000.0070.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0040.0000.0000.0000.0000.0000.0000.0170.0000.0000.0000.0000.0110.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0020.0040.0000.0000.0000.0000.0340.0000.0060.0000.0180.0000.0000.0000.0050.0000.0000.0110.0060.0000.0000.0000.0000.0000.0030.0000.0000.0000.0000.0030.0000.0020.005
Activity Type_Fishing0.0810.0730.0280.0000.0000.0780.0860.0000.0190.0130.1020.0440.0710.2060.0450.0000.0000.0000.0110.0000.0000.0000.0000.0050.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0120.0001.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0020.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0020.0000.0000.0000.0000.0140.0000.0110.0000.0000.0000.0000.0060.0000.0000.0000.0000.0080.0030.0000.0120.0000.0000.0000.0050.0000.0000.0170.0000.0000.0000.0000.0000.0040.0030.0140.0040.0000.0000.0040.0000.0000.0000.0000.0000.0000.0090.0160.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0160.000
Activity Type_Flight - HETS0.0000.0000.0000.0000.0000.0000.0000.0250.0000.0001.0000.0300.0161.0001.0001.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0001.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0080.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0120.000
Activity Type_Flight - Hang-gliding/Parapenting0.0000.0000.0000.0000.0000.0190.0120.0450.0000.0001.0000.0100.0310.0001.0001.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0001.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0220.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0120.0000.0000.0000.0000.0000.0000.0000.0000.0000.0040.0000.0000.0000.0000.000
Activity Type_Flight - Helicopter0.0000.0000.0000.0000.0000.0260.0300.0310.0000.0000.0230.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0020.0000.0000.0000.0001.0000.0000.0000.0000.0000.0000.0000.0000.0060.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0120.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0020.0000.0100.0000.0020.0000.0000.0000.0000.0000.0000.0120.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.000
Activity Type_Flight - Sightseeing/Site Access0.0000.0000.0000.0000.0000.0270.0270.0030.0070.0000.0250.0000.0000.0170.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0001.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0190.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0070.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.000
Activity Type_Golfing0.0910.0600.0000.0000.0000.1150.1090.0750.0130.0450.1000.1270.0720.2620.0790.0160.0110.0130.0000.0000.0000.0000.0140.0420.0080.0000.0000.0000.0000.0000.0000.0000.0040.0030.0060.0090.0000.0100.0000.0110.1060.0030.0000.0000.0000.0000.0001.0000.0010.0000.0050.0100.0130.0410.0040.0000.0000.0000.0000.0000.0000.0000.0000.0100.0000.0000.0360.0000.0000.0000.0000.0120.0000.0000.0000.0310.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0030.0000.0000.0000.0000.0000.0000.0680.0000.0000.0050.0000.0450.0000.0070.0080.0000.0020.0040.0000.0160.0140.0060.0000.0100.0050.0130.0040.0040.0320.0220.0050.0000.0000.0450.0680.0000.0280.0080.0140.0000.0010.0000.0140.0010.0090.0340.0300.0030.0080.0090.0060.0000.0200.0060.0040.0250.0000.0190.0000.0160.014
Activity Type_Heritage Activity - Bird Watching0.0130.0190.0000.0000.0000.0510.0480.0350.0000.0320.0750.0380.0800.0560.0300.1520.0000.0000.0000.0000.0000.0000.0000.0030.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0130.0000.0000.0000.0000.0000.0000.0011.0000.0000.0050.0000.0220.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0060.0000.0000.0000.0000.0030.0000.0000.0000.0000.0000.0000.0100.0000.0400.0000.0000.0000.0000.0000.0060.0000.0000.0000.0000.0000.0000.0000.0100.0070.0100.0000.0080.0000.0000.0000.0180.0000.0000.0040.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0150.0000.0000.0130.000
Activity Type_Heritage Activity - History Activities0.0900.1810.0020.0000.0000.1880.2130.0160.0450.0000.0390.0000.0000.0110.0000.0000.0000.0000.0000.0000.0000.0000.0000.0080.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0240.0000.0000.0000.0000.0000.0000.0000.0001.0000.0000.0160.0000.0050.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0060.0000.0000.0000.0000.0000.0000.0000.0000.0050.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0050.0000.0000.0000.0000.0000.0000.0150.0000.0000.0000.0000.0090.0000.0000.0000.0000.0000.0210.0000.0000.0000.0000.0000.0000.0000.0050.0000.0000.0050.0080.0000.0000.0130.0000.0000.0000.0000.0000.0100.0000.0000.0000.0000.0000.0000.0110.0000.0000.0000.0050.0000.0000.0070.0000.0000.0030.0000.0000.0000.0000.000
Activity Type_Heritage Activity - Photography and Art0.0230.0110.0090.0000.0000.0680.0670.0910.0010.0110.0390.0400.0800.0700.0470.0270.0000.0000.0000.0000.0000.0000.0000.0130.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0050.0000.0000.0000.0000.0000.0000.0050.0050.0001.0000.0000.0000.0090.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0100.0000.0000.0000.0000.0000.0000.0000.0000.0090.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0090.0000.0000.0000.0000.0000.0000.0210.0000.0000.0000.0000.0130.0000.0000.0000.0000.0000.0000.0000.0030.0000.0000.0000.0000.0000.0000.0000.0000.0000.0070.0000.0000.0000.0020.0110.0000.0320.0000.0020.0000.0190.0000.0020.0000.0000.0000.0100.0000.0120.0000.0160.0000.0070.0000.0000.0000.0000.0050.0000.0000.005
Activity Type_Heritage Activity - Sightseeing0.0190.0470.0000.0000.0000.0580.0580.0220.0010.0230.0800.0140.0240.0400.0350.0150.0040.0050.0000.0000.0000.0000.0060.0210.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0010.0000.0000.0000.0030.0510.0000.0000.0000.0000.0000.0000.0100.0000.0160.0001.0000.0000.0140.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0180.0000.0000.0000.0000.0000.0000.0000.0000.0150.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0120.0000.0000.0000.0000.0000.0000.0320.0180.0000.0000.0000.0220.0000.0000.0000.0000.0000.0000.0000.0110.0000.0000.0000.0050.0000.0000.0000.0000.0100.0160.0000.0000.0070.0000.0000.0000.0010.0000.0000.0000.0000.0000.0000.0000.0020.0020.0000.0030.0000.0000.0010.0000.0000.0000.0000.0080.0000.0100.0000.0000.011
Activity Type_Heritage Activity - Wildlife Observation0.0230.0600.0000.0000.0240.1000.1250.1310.0050.0350.1720.0630.1160.0790.0560.0290.0070.0080.0000.0000.0000.0000.0090.0270.0040.0000.0000.0000.0000.0000.0000.0000.0000.0000.0010.0000.0000.0000.0000.0060.0510.0000.0000.0000.0000.0000.0000.0130.0220.0000.0000.0001.0000.0200.0000.0000.0000.0000.0000.0000.0000.0000.0000.0060.0000.0000.0230.0000.0000.0000.0000.0000.0000.0000.0000.0210.0000.0000.0200.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0020.0210.0000.0000.0000.0000.0000.0000.0460.0000.0000.0000.0000.0300.0000.0000.0040.0000.0000.0000.0000.0050.0000.0010.0000.0000.0000.0030.0000.0000.0050.0190.0000.0010.0070.0110.0230.0000.0710.0030.0050.0000.0000.0000.0040.0000.0000.0140.0000.0000.0000.0000.0040.0000.0080.0000.0000.0180.0000.0110.0030.0050.006
Activity Type_Hiking / Walking0.1040.1520.0500.0270.0000.2170.2290.1350.0000.0560.2920.2360.2250.1720.1780.1450.0000.0100.0000.0000.0060.0000.0040.0760.0160.0000.0000.0000.0000.0000.0000.0000.0090.0000.0020.0010.0000.0050.0000.0220.1930.0070.0000.0000.0000.0060.0000.0410.0000.0050.0090.0140.0201.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0210.0000.0000.0550.0000.0000.0000.0000.0080.0000.0000.0000.0600.0000.0010.0000.0000.0000.0000.0000.0070.0040.0060.0000.0000.0000.0000.0000.0000.0590.0000.0000.0000.0000.0010.0000.1290.0040.0000.0130.0000.0880.0000.0740.0190.0000.0000.0070.0040.0180.1140.0100.0000.0000.0130.0080.0000.0000.0520.0350.0000.0070.0420.0320.1020.0060.0670.0020.0680.0170.0350.0000.0090.0000.0220.0540.1030.0050.0350.0320.0000.0000.0150.0050.0020.0370.0040.0350.0020.0980.007
Activity Type_Horse Riding - Day Trip0.0100.0060.0140.0000.0000.0220.0160.0190.0000.0190.0400.0650.0540.0460.0110.0280.0000.0000.0000.0000.0000.0000.0000.0100.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0290.0000.0000.0000.0000.0000.0000.0040.0000.0000.0000.0000.0000.0001.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0050.0000.0000.0000.0000.0000.0000.0000.0000.0080.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0080.0000.0000.0000.0000.0000.0000.0190.0000.0000.0000.0000.0100.0000.0040.0020.0000.0000.0000.0000.0000.0120.0000.0000.0000.0000.0000.0000.0000.0080.0000.0000.0000.0000.0000.0160.0000.0000.0000.0160.0000.0000.0000.0020.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0060.0000.0040.0000.0000.008
Activity Type_Horse Riding - Multiday0.0000.0000.0160.0000.0000.0000.0000.0320.0000.0000.0280.0360.0150.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0080.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0001.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0040.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0060.0000.0000.0000.0070.0000.0000.0000.0190.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0060.0080.0000.0000.0000.0000.0000.000
Activity Type_Ice Skating0.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0001.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0940.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0060.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.000
Activity Type_Kayaking - Coastal0.0120.0500.0000.0000.0000.0560.0560.0130.0430.0300.0000.0270.0000.0040.0470.0000.0000.0000.0000.0000.0190.0000.0350.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0070.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0001.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0030.0000.0000.0000.0000.0000.0000.0000.0400.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0040.0000.0000.0000.0090.0000.0000.0000.0000.0000.0000.0000.0080.0000.0000.0000.0030.0000.0000.0000.0000.0000.0000.0000.0000.0000.000
Activity Type_Kayaking - Flatwater0.0000.0080.0000.0000.0000.0130.0000.0300.0000.0000.0100.0160.0280.0370.0000.0140.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0570.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0090.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0001.0000.0000.0000.0000.0000.0000.0000.2430.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0040.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0090.0000.0130.0000.0050.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0140.0000.0000.0000.0000.0000.0000.0000.0000.0140.000
Activity Type_Kayaking - Swiftwater0.1760.1760.0070.0000.0000.1500.1700.0000.0000.0150.0570.0290.1130.0001.0001.0000.0000.0000.0000.0000.0000.0000.0120.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0001.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0100.0000.0000.0000.0000.0000.0000.0000.0000.0000.0010.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.000
Activity Type_Mooring0.0000.0260.0000.0000.0000.0380.0350.0000.0000.0000.0000.0330.0130.0120.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0001.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0270.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.000
Activity Type_Not Applicable0.0630.0220.0000.0000.0000.0800.0820.0140.0060.0080.0000.0500.0430.0450.0281.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0020.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0001.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0110.0000.0000.0020.0000.0000.0000.0020.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.000
Activity Type_Orienteering / Geocaching0.0000.0000.0000.0000.0000.0000.0000.0000.0000.0001.0000.0001.0000.0001.0001.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0001.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.000
Activity Type_Other0.0900.1110.0000.0000.0000.1260.1320.0600.0570.0780.1030.0710.0430.0550.0580.0520.0040.0020.0000.0000.0000.0000.0060.0200.0090.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0050.0000.0040.0520.0000.0000.0000.0000.0000.0000.0100.0000.0000.0000.0000.0060.0210.0000.0000.0000.0000.0000.0000.0000.0000.0001.0000.0240.0000.0110.0000.0000.0000.0000.0000.0000.0000.0000.0150.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0150.0000.0000.0000.0000.0000.0000.0330.0000.0000.0000.0000.0230.0000.0000.0290.0060.0240.0050.0000.0030.0000.0000.0000.0000.0000.0000.0370.0050.0160.0030.0000.0050.0000.0030.0370.0000.0080.0000.0000.0000.0000.0130.0000.0000.0050.0000.0380.0060.0000.0220.0090.0120.0580.0140.0000.0080.0000.0200.0000.0080.005
Activity Type_Paddleboarding - Coastal0.0320.0260.0000.0000.0000.0490.0470.0000.0161.0001.0001.0001.0001.0001.0001.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0241.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0240.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.000
Activity Type_Paddleboarding - Flatwater0.0000.0000.0000.0000.0000.0000.0000.0140.0000.0000.0000.0190.0190.0390.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0080.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.2430.0000.0000.0000.0000.0000.0001.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0280.0000.0030.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0030.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0080.000
Activity Type_Park Operations0.1040.1760.0650.0000.0310.2730.3010.1660.0030.0910.3740.0920.0820.1530.1790.0800.0140.0180.0030.0000.0040.0000.0220.0630.0150.0000.0030.0000.0000.0000.0000.0000.0090.0080.0100.0150.0000.0220.0000.0190.1450.0080.0000.0000.0000.0000.0000.0360.0000.0060.0100.0180.0230.0550.0050.0000.0000.0000.0000.0000.0000.0000.0000.0110.0000.0001.0000.0230.0000.0020.0000.0190.0000.0000.0000.0500.0000.0030.0000.0030.0060.0000.0000.0000.0000.0040.0000.0000.0000.0000.0000.0000.0510.0000.0000.0000.0000.0000.0000.1100.0020.0000.0060.0000.0740.0000.0080.0060.0000.0240.0060.0150.0850.0930.1930.0550.1220.2010.0210.0140.0000.0430.0140.0000.0130.0000.0150.0000.0100.0500.1200.0200.0000.0000.0000.0140.0000.1470.0260.0470.1480.0030.0230.0000.0150.0120.0040.0110.0230.0090.0220.0150.0840.021
Activity Type_Park Ops - Avalanche Forecasting0.0000.0000.0000.0000.0000.0130.0120.0230.0000.0000.0311.0001.0000.0420.0380.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0020.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0231.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0190.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0050.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.000
Activity Type_Park Ops - Avalanche Control0.0000.0000.0000.0000.0000.0370.0440.0170.0000.0070.0000.0000.0000.0120.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0001.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0050.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0130.0000.0000.0000.0000.0000.0000.000
Activity Type_Park Ops - Search and Rescue0.0210.0160.0000.0000.0000.0330.0300.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0020.0000.0001.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0170.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.000
Activity Type_Park Ops - Training0.0000.0190.0000.0000.0000.0180.0120.0120.0000.0140.0450.0150.0000.0000.0000.0200.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0020.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0001.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0020.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0160.0000.0000.0000.0080.0000.0000.0000.0000.0000.0000.0030.0000.0000.000
Activity Type_Picnicking / BBQ0.0210.0520.0020.0000.0000.0890.0900.0640.0030.0330.0850.1170.1380.1850.0480.0100.0050.0000.0000.0000.0000.0000.0070.0240.0030.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0030.0000.0040.0000.0050.0590.0000.0000.0000.0000.0000.0000.0120.0000.0000.0000.0000.0000.0080.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0190.0000.0000.0000.0001.0000.0000.0000.0000.0180.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0230.0000.0000.0000.0030.0140.0000.0000.0000.0000.0000.0000.0390.0000.0000.0000.0000.0270.0000.0000.0000.0000.0260.0000.0000.0430.0250.0000.0000.0000.0000.0000.0000.0000.0170.0170.0000.0000.0000.0070.0190.0000.0270.0020.0030.0000.0000.0000.0000.0130.0000.0120.0120.0040.0000.0030.0000.0000.0040.0000.0000.0070.0000.0000.0090.0240.001
Activity Type_Playground Activities0.0000.0000.0000.0000.0000.0060.0050.0140.0000.0000.0000.0220.0000.0000.0160.0000.0000.0000.0000.0000.0000.0000.0000.0020.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0090.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0001.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0030.0000.0000.0000.0000.0030.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0020.0050.0000.0000.0000.0070.0000.0000.0000.0060.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0130.0000.0000.0000.0000.0000.0000.0000.000
Activity Type_Rafting - Flatwater0.0000.0000.0000.0000.0000.0000.0000.0250.0000.0000.0000.0001.0001.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0001.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0080.0000.000
Activity Type_Rafting - Swiftwater0.0000.0000.0000.0000.0000.0000.0000.0110.0000.0150.0640.0000.0130.0120.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0030.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0001.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0030.0000.0090.0000.0050.0000.0000.0000.0040.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.000
Activity Type_Railway0.1280.1040.0000.0100.0000.1620.1690.1230.0110.1270.3080.1790.0770.6300.2790.0430.0170.0190.0000.0000.0030.0000.0210.0600.0130.0000.0010.0000.0000.0000.0000.0000.0080.0070.0100.0130.0000.0180.0000.0170.1540.0070.0020.0000.0000.0000.0000.0310.0000.0050.0090.0150.0210.0600.0080.0000.0000.0000.0000.0000.0000.0000.0000.0150.0000.0000.0500.0000.0000.0000.0000.0180.0000.0000.0001.0000.0040.0010.0000.0000.0050.0000.0000.0000.0000.0020.0000.0000.0000.0000.0000.0000.0250.0000.0000.0000.0000.0000.0000.0980.0000.0000.0090.0000.0550.0000.0120.0020.0000.0000.0080.0040.0050.0180.0100.0000.0040.0090.0320.0080.0330.0450.0880.0000.0360.0050.0360.0390.0000.0370.0120.0110.0000.0050.0000.0090.0050.0140.0570.0470.0000.0040.0090.0260.0000.0200.0550.0080.0360.0000.0300.0150.0280.006
Activity Type_Research - Scientific/Social0.0410.0470.0290.0000.0000.0680.0850.0310.0000.0290.0570.0690.0510.0690.0620.0700.0000.0000.0000.0000.0000.0000.0000.0070.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0200.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0041.0000.0430.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0140.0000.0000.0000.0000.0080.0000.0000.0000.0000.0000.0000.0000.0000.0270.0000.0480.0230.0000.0000.0340.0000.0040.0000.0000.0060.0010.0040.0220.0000.0040.0000.0000.0000.0040.0000.0160.0000.0000.0000.0040.0000.0000.0000.0000.0000.0000.0000.0000.0020.0080.0210.0000.0000.006
Activity Type_Resource Harvesting - Hunting/Fishing/Gathering/Trapping0.1280.0470.0000.0000.0000.1450.2150.0350.0770.0320.3890.0750.0700.0720.0570.0170.0000.0000.0000.0000.0000.0000.0000.0050.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0160.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0010.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0030.0000.0000.0000.0000.0000.0000.0000.0000.0010.0431.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0010.0000.0000.0000.0000.0000.0000.0100.0000.0000.0000.0000.0050.0000.0000.0000.0000.0000.0000.0000.0020.0080.0000.0000.0000.0000.0000.0320.0000.0010.0000.0000.0000.0000.0000.0160.0000.0000.0000.0110.0000.0000.0000.0000.0000.0000.0050.0000.0000.0000.0000.0000.0000.0000.0000.0140.0000.0000.0000.0000.0000.000
Activity Type_Roller Sports0.0000.0000.0000.0000.0000.0000.0000.0000.0040.0101.0000.0550.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0040.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0200.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0001.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0030.0000.0000.0000.0000.0000.0000.0000.0000.0000.0100.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.000
Activity Type_Running - Road0.0000.0000.0000.0000.0000.0000.0000.0150.0150.0000.0000.0390.0340.0280.0000.0510.0000.0000.0000.0000.0000.0000.0000.0040.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0140.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0030.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0001.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0100.0000.0000.0000.0000.0050.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0040.0000.0000.0000.0000.0050.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0060.0000.0000.0000.0000.0000.0000.0090.0000.0000.0000.0000.0000.0000.0000.000
Activity Type_Running - Trail0.0000.0000.0150.0000.0000.0310.0470.0150.0000.0000.0360.0900.1010.0220.0170.0860.0000.0000.0000.0000.0000.0000.0000.0080.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0080.0000.0000.0230.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0060.0000.0000.0000.0000.0000.0000.0000.0000.0050.0000.0000.0000.0001.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0120.0000.0050.0000.0000.0000.0000.0000.0000.0140.0000.0000.0000.0000.0090.0000.0000.0000.0000.0000.0000.0000.0000.0150.0000.0000.0000.0000.0000.0000.0000.0050.0050.0000.0000.0130.0000.0150.0000.0000.0000.0180.0000.0030.0000.0000.0000.0000.0020.0000.0000.0000.0000.0000.0000.0050.0000.0000.0030.0000.0000.0000.0110.000
Activity Type_Sail Sports - Wind / Kite Surfing0.0000.0000.0000.0000.0000.0110.0140.0000.0000.0000.0001.0001.0001.0001.0001.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0001.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0150.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0150.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.000
Activity Type_Scrambling0.0000.0000.0000.0000.0000.0000.0000.0230.0000.0001.0001.0001.0001.0001.0001.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0001.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.000
Activity Type_Skiing - Crosscountry0.0100.0180.0000.0000.0000.0310.0270.0290.0000.0200.0950.0660.0350.0870.0340.0290.0000.0000.0000.0000.0000.0000.0000.0060.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0450.0000.0190.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0070.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0001.0000.0000.0000.0000.0230.0000.0000.0000.0000.0030.0000.0000.0000.0000.0000.0000.0120.0000.0000.0000.0000.0030.0000.0100.0000.0190.0060.0000.0000.0000.0140.0000.0000.0000.0000.0000.0000.0000.0040.0070.0000.0000.0030.0030.0150.0000.0000.0000.0100.0000.0000.0000.0140.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0060.002
Activity Type_Skiing/Boarding - Backcountry0.0020.0020.0230.0000.0000.0960.1580.0980.0000.0000.0160.0170.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0040.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0140.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0040.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0001.0000.0000.0000.0000.0000.0250.0000.0000.0000.0000.0000.0000.0000.0000.0000.0090.0000.0000.0000.0000.0050.0000.0000.0000.0000.0000.0000.0000.0000.0610.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0100.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0160.0050.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.002
Activity Type_Skiing/Boarding - Ski Resort In Bounds0.0050.0070.0080.0000.0000.0320.0100.0270.0000.0000.0470.0350.0170.0520.0000.0480.0000.0000.0000.0000.0000.0000.0000.0050.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0180.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0060.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0040.0000.0000.0000.0000.0000.0000.0000.0000.0020.0000.0000.0000.0000.0000.0000.0000.0000.0001.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0110.0000.0000.0000.0000.0060.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0020.0000.0000.0000.0000.0000.0140.0000.0010.0000.0120.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0190.0000.0050.0000.0000.0000.0110.0090.0000.0000.012
Activity Type_Skiing/Boarding - Ski Resort Out of Bounds0.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0620.0250.0001.0001.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0001.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0240.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0210.0000.0000.000
Activity Type_Sledding/Tobogganning0.0000.0000.0260.0000.0000.0000.0000.0100.0000.0000.0150.0290.0260.0270.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0040.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0940.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0230.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0230.0000.0000.0001.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0520.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0410.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.000
Activity Type_Snowmobiling0.0000.0260.0000.0000.0000.0380.0350.0000.0000.0240.0430.0110.0401.0001.0001.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0001.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.000
Activity Type_Snowshoeing0.0000.0130.0000.0000.0000.0290.0220.0090.0000.0000.0000.0340.1020.0240.0551.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0250.0000.0000.0000.0001.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0010.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0150.0000.0000.0000.0000.0000.0000.0130.0000.0060.0000.0000.0000.0000.0000.0000.0000.0130.0000.0000.0000.0000.0060.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.000
Activity Type_Special Event - Participative Audience0.0120.0080.0000.0000.0000.0510.0540.0040.0000.0000.0000.0490.0250.0300.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0100.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0120.0000.0000.0000.0000.0000.0000.0000.0000.0001.0000.0000.0000.0000.0000.0000.0000.0000.0000.0050.0000.0000.0000.0000.0000.0000.0000.0000.0000.0030.0000.0000.0090.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0080.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0040.0000.0000.0000.0070.000
Activity Type_Special Events - Passive Audience0.0130.0330.0000.0000.0000.0400.0410.0000.0000.0000.0000.0000.0270.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0070.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0020.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0030.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0001.0000.0030.0000.0000.0000.0000.0000.0000.0030.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0040.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0050.0000.0000.0000.0000.0000.0000.0000.000
Activity Type_Stakeholder Operations0.1300.0960.0150.0000.0000.1590.1590.1260.0100.0580.1930.1480.1110.1150.0590.0560.0170.0180.0000.0000.0030.0000.0210.0610.0000.0000.0010.0000.0000.0000.0000.0000.0060.0070.0080.0120.0000.0140.0000.0160.1520.0040.0020.0000.0000.0000.0000.0030.0000.0050.0090.0120.0210.0590.0080.0000.0000.0000.0000.0000.0000.0000.0000.0150.0000.0000.0510.0000.0000.0000.0000.0140.0000.0000.0000.0250.0000.0010.0000.0000.0050.0000.0000.0030.0000.0000.0000.0000.0000.0000.0000.0031.0000.0000.0000.0000.0000.0000.0000.0970.0080.0000.0090.0000.0650.0000.0090.0000.0000.0050.0080.0040.0100.0040.0100.0000.0120.0080.0100.0130.0000.0430.0290.0000.0000.0030.0000.0000.0000.0300.0090.0190.0000.0000.0000.0120.0030.0080.0370.0360.0140.0030.0070.0000.0000.0740.0000.0000.0280.0330.0700.0000.0190.018
Activity Type_Surfing0.0000.0420.0700.0000.0000.0410.0380.0030.0000.0130.0160.0690.0100.0000.0001.0000.0000.0220.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0001.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0060.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0040.0000.0080.0000.0000.0000.0000.0000.0000.0000.0000.0000.0260.0080.0000.0000.0220.0000.0000.0100.0000.0000.0000.0000.0000.0000.000
Activity Type_Swimming - Cliff Jumping0.0000.0000.0000.0000.0000.0000.0000.0000.0001.0001.0000.0000.0001.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0001.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.000
Activity Type_Swimming - Coastal0.0320.0260.0000.0000.0000.0490.0470.0000.0000.0240.0000.0380.0001.0001.0001.0000.0000.0190.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0001.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0090.0000.0000.0000.0000.0000.0000.0000.000
Activity Type_Swimming - Facilities0.0000.0000.0000.0000.0000.0000.0060.0100.0000.0000.0390.0000.0070.0220.0830.0000.0000.0030.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0070.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0001.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0110.0000.0000.0000.0000.0140.0000.0000.0000.0000.0000.0000.0000.0000.0070.0000.0000.0000.0000.0000.0000.0000.0120.0000.0000.0010.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0030.0000.000
Activity Type_Swimming - Flat Water0.0000.0180.0000.0000.0000.0260.1470.0140.0000.0000.0000.0300.0170.0000.0000.0060.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0120.0000.0140.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0010.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0280.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0001.0000.0000.0000.0000.0000.0000.0000.0020.0000.0000.0000.0000.0000.0070.0000.0000.0000.0000.0000.0000.0000.0080.0070.0000.0000.0000.0000.0020.0000.0000.0060.0000.0000.0000.0000.0000.0000.0000.0000.0100.0000.0020.0000.0000.0030.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.000
Activity Type_Swimming - Swiftwater0.0000.0350.0000.0000.0000.0520.0500.0000.0030.0090.0000.0000.0000.0000.0241.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0060.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0001.0000.0090.0000.0000.0000.0000.0000.0000.0000.0000.0000.0060.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.021
Activity Type_Townsite Activity0.0890.1370.0150.0130.0000.2330.2160.1620.0260.1650.2670.1750.1300.2750.3150.1510.0390.0420.0080.0030.0120.0000.0470.1290.0300.0040.0100.0040.0000.0000.0000.0000.0200.0180.0220.0300.0000.0270.0000.0380.3290.0170.0110.0000.0000.0000.0000.0680.0060.0150.0210.0320.0460.1290.0190.0040.0000.0030.0040.0000.0000.0000.0000.0330.0000.0030.1100.0000.0000.0000.0000.0390.0030.0000.0000.0980.0140.0100.0000.0100.0140.0000.0000.0120.0090.0110.0000.0000.0000.0010.0050.0030.0970.0000.0000.0000.0000.0000.0091.0000.0050.0000.0180.0000.1410.0000.0150.0190.0010.0030.0000.0070.0260.0360.0230.0050.0230.0220.0140.0030.0080.0890.0770.0130.0140.0150.0950.2320.0080.0500.0280.1100.0060.0130.0000.0430.0340.0180.0900.0640.0240.0210.0180.0080.0000.0000.0150.0150.0730.0000.0130.0300.0360.034
Activity Type_Tram/Ski Lift/Gondola0.0000.0000.0000.0000.0000.0000.0000.0460.0000.0000.0000.0000.0140.0240.0000.0000.0000.0000.0000.0000.0000.0000.0000.0040.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0150.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0180.0000.0040.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0020.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0080.0000.0000.0000.0000.0000.0000.0051.0000.0000.0000.0000.0040.0000.0000.0000.0000.0000.0000.0090.0000.0000.0000.0000.0000.0000.0000.0050.0000.0000.0000.0000.0000.0000.0000.0050.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0140.0000.0000.0000.0000.0240.0150.0000.000
Activity Type_Tubing / River Drifting0.0000.0110.0000.0000.0000.0220.0340.0200.0000.0240.0000.0520.0001.0001.0001.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0001.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0040.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0070.0000.0000.000
Activity Type_Unknown0.0570.1260.0000.0000.0000.0880.1400.0480.0440.0550.0770.0830.0620.0460.0520.0620.0000.0000.0000.0000.0140.0000.0000.0130.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0330.0000.0000.0000.0220.0000.0190.0050.0000.0000.0000.0000.0000.0130.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0060.0000.0000.0000.0000.0000.0000.0000.0000.0090.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0090.0000.0000.0000.0000.0000.0000.0180.0000.0001.0000.0000.0140.0000.0000.0210.0000.0210.0000.0510.0070.0000.0000.0040.0160.0000.0070.0000.0000.0060.0000.0000.0060.0000.0020.0280.0000.0000.0000.0000.0000.0000.0220.0130.0000.0000.0000.0170.0250.0000.0290.0190.0050.0050.0000.0000.0020.0040.0010.0000.0050.000
Activity Type_Via-Ferrata0.0000.0000.0000.0000.0000.0000.0000.0120.0000.0220.1250.0000.0161.0001.0001.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0001.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.000
Activity Type_nan0.2140.1630.0140.0170.0000.3780.3380.1510.0070.2660.3270.1940.1950.3070.4501.0000.0250.0280.0040.0000.0070.0000.0310.0870.0190.0000.0000.0000.0000.0000.0000.0000.0120.0110.0120.0200.0000.0250.0000.0250.2190.0110.0060.0000.0000.0000.0000.0450.0030.0090.0130.0220.0300.0880.0100.0000.0000.0000.0000.0000.0000.0000.0000.0230.0000.0000.0740.0000.0000.0000.0000.0270.0030.0000.0000.0550.0080.0050.0000.0050.0090.0000.0000.0030.0050.0060.0000.0000.0000.0000.0000.0000.0650.0000.0000.0000.0000.0020.0000.1410.0040.0000.0140.0001.0000.0000.0060.0050.0060.0220.0000.0060.0340.0100.0120.0040.0270.0140.0020.0120.0070.0380.0160.0000.0200.0000.0600.0080.0160.0250.0180.1050.0000.0000.0000.0360.0090.0210.0860.0710.0000.0190.0000.0000.0030.0880.0130.0310.0120.0040.1370.0260.0140.112
Response Type_0.0000.0720.0670.0000.0000.0730.0720.0150.0000.0001.0000.0380.0240.0331.0001.0000.0000.0000.0000.0000.0000.0000.0000.0100.0000.0720.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0001.0000.0000.0000.0000.0000.0000.0000.0260.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0050.0000.0000.000
Response Type_Assist Visitor0.0370.0690.0300.0000.0000.0890.0960.0400.0110.0080.0660.0950.0730.0440.0300.0590.0000.0160.0020.0080.0000.0000.0180.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0170.0070.0000.0140.0000.0000.0240.0000.0000.0000.0000.0000.0000.0070.0000.0000.0000.0000.0000.0740.0040.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0080.0000.0000.0000.0000.0000.0000.0000.0000.0120.0000.0000.0000.0000.0000.0000.0000.0100.0000.0000.0000.0000.0000.0000.0000.0000.0090.0000.0000.0000.0000.0000.0000.0150.0000.0000.0000.0000.0060.0001.0000.0080.0080.0000.0000.0090.0020.0110.0000.0000.0000.0000.0000.0000.0260.0090.0000.0000.0000.0290.0090.0320.0000.0250.0000.0000.0000.0000.0000.0000.0000.0000.0040.0080.0000.0000.0110.0000.0000.0000.0090.0110.0000.0000.0000.0010.0180.000
Response Type_Assist other Agency0.0300.1120.0130.0000.0000.1180.1220.0770.2050.0930.0330.1150.0870.0650.0660.0610.0020.0100.0920.0000.0100.0000.0080.0090.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0210.0000.0450.0000.0000.0000.0000.0000.0120.0000.0080.0000.0000.0000.0000.0040.0190.0020.0000.0000.0400.0000.0000.0000.0000.0000.0290.0000.0000.0060.0000.0000.0000.0000.0000.0000.0000.0000.0020.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0190.0000.0000.0210.0000.0050.0000.0081.0000.0070.0030.0020.0290.0000.0000.0050.0000.0320.0000.0120.0030.0420.0080.0040.0080.0150.0250.0090.0380.0100.0170.0000.0130.0000.0000.0000.0010.0000.0050.0060.0000.0180.0000.0530.0630.0000.0030.0840.0720.0030.0000.0040.0030.0270.023
Response Type_Assist other Field Unit0.0000.0000.0130.0000.0000.0150.0080.0230.0030.0050.0000.0200.0440.0000.0000.0160.0000.0040.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0060.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0190.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0010.0000.0000.0000.0000.0060.0000.0080.0071.0000.0000.0000.0000.0000.0000.0000.0000.0040.0000.0020.0000.0000.0000.0000.0000.0070.0130.0000.0030.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0060.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.000
Response Type_Attractant Management0.0670.0710.1110.1100.0000.0750.1020.2300.0050.0500.0440.1230.1590.1600.0450.0520.0040.0180.0000.0000.0370.0000.0340.0230.0280.0000.0000.0000.0000.0000.0000.0000.0190.0000.0000.0010.0000.0000.0000.0000.0290.0000.0080.0000.0000.0000.0000.0020.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0240.0000.0000.0240.0000.0000.0000.0000.0260.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0060.0000.0000.0000.0000.0000.0000.0030.0000.0050.0000.0000.0000.0000.0000.0060.0030.0000.0000.0210.0000.0220.0000.0000.0030.0001.0000.0190.0000.0530.0000.0000.0000.0000.0000.0000.0160.0000.0080.0060.0000.0010.0120.0030.0350.0000.0310.0000.0140.0000.0000.0130.0000.0000.0300.0050.0120.0000.0000.0010.0140.0410.0070.0050.0000.0040.0000.0030.0040.0180.013
Response Type_Aversive Conditioning0.0200.0700.0840.0820.0000.0770.0840.0250.0000.0180.1310.0400.0490.0250.1390.0080.0000.0000.0000.0000.0280.0000.0000.0180.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0010.0000.0030.0000.0000.0000.0000.0040.0000.0210.0000.0000.0000.0070.0000.0000.0000.0000.0000.0000.0000.0000.0000.0050.0000.0000.0060.0000.0000.0000.0000.0000.0000.0000.0000.0080.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0080.0000.0000.0000.0000.0070.0000.0000.0000.0000.0000.0000.0000.0000.0000.0020.0000.0191.0000.0000.0020.0000.0000.0000.0000.0000.0320.0000.0000.0350.0110.0000.0000.0090.0050.0060.0000.0280.0000.0080.0000.0000.0000.0020.0000.0000.0180.0020.0000.0000.0000.0000.0230.0000.0000.0000.0000.0000.0000.0000.0000.007
Response Type_Capture and transport to captivity0.0380.0370.0180.0000.0000.0860.0860.0890.0120.0860.0190.0380.0460.0000.0160.0000.0000.0190.0090.0180.0000.0000.0000.0070.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0120.0070.0000.0000.0000.0000.0000.0000.0000.0100.0000.0000.0000.0000.0040.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0150.0000.0000.0000.0000.0000.0000.0000.0000.0040.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0040.0000.0000.0000.0000.0000.0000.0070.0090.0000.0510.0000.0060.0000.0090.0290.0000.0000.0001.0000.0000.0000.0000.0000.0000.0000.0000.0000.0130.0000.0000.0000.0000.0260.0030.0200.0150.0000.0000.0000.0000.0000.0000.0000.0000.0000.0020.0050.0050.0000.0000.0000.0000.0000.0310.0100.0020.0000.0180.0000.0000.000
Response Type_Clean Up0.1480.1670.0000.0000.0000.3220.3290.3450.0000.1860.3670.1650.1990.2320.1280.1490.0040.0000.0000.0000.0000.0000.0000.0040.0000.0000.0020.0000.0000.0000.0000.0000.0340.0000.0000.0060.0070.0100.0000.0080.0130.0000.0120.0000.0000.0000.0000.0160.0000.0000.0030.0110.0050.0180.0000.0000.0060.0000.0000.0100.0000.0000.0000.0030.0000.0000.0850.0190.0000.0000.0000.0430.0000.0000.0000.0050.0000.0020.0000.0000.0000.0150.0000.0000.0000.0000.0000.0000.0000.0000.0090.0000.0100.0000.0000.0000.0000.0000.0000.0260.0000.0000.0070.0000.0340.0260.0020.0000.0000.0530.0020.0001.0000.1590.3790.0000.2310.3970.0090.0000.0080.0260.0300.0020.0020.0000.0200.0830.0000.1040.0050.0490.0000.0000.0000.0920.0000.2800.0340.0250.2590.0060.0040.0170.0050.0200.0140.0000.0110.0000.0160.0050.1320.022
Response Type_Close Area0.1530.1460.2170.0690.0000.3090.3090.3240.0000.0930.4860.1150.1440.1880.0920.0910.0030.0000.0000.0000.0070.0000.0440.0170.0000.0000.0390.0000.0000.0000.0040.0220.0000.0070.0350.0030.0000.0200.0000.0080.0710.0000.0000.0000.0000.0000.0000.0140.0400.0000.0000.0000.0000.1140.0120.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0930.0000.0000.0000.0000.0250.0000.0000.0000.0180.0270.0080.0000.0000.0150.0000.0000.0140.0610.0000.0000.0520.0000.0000.0000.0000.0040.0000.0000.0000.0110.0000.0000.0360.0000.0000.0000.0000.0100.0000.0110.0000.0000.0000.0000.0000.1591.0000.3990.0100.2190.4040.0060.0010.0000.0170.0000.0020.0060.0620.0130.0630.0000.1210.0030.0270.0000.0070.0000.0240.0000.3330.0060.0120.2600.0060.0030.0040.0000.0110.0000.0220.0000.0000.0160.0090.2120.022
Response Type_Close Road0.3450.3340.0000.0000.0000.7110.7110.2990.0020.1370.5970.0000.0000.0000.2250.0000.0000.0000.0000.0000.0000.0000.0010.0130.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0330.0000.0000.0000.0000.0000.0000.0060.0000.0000.0000.0000.0010.0100.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.1930.0000.0000.0000.0000.0000.0000.0000.0000.0100.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0100.0000.0000.0000.0000.0000.0000.0230.0000.0000.0000.0000.0120.0000.0000.0050.0000.0000.0000.0000.3790.3991.0000.0000.5080.9320.0000.0000.0050.0090.0080.0000.0000.0070.0080.0350.0000.2320.0000.0270.0000.0000.0000.0030.0000.6540.0140.0080.6020.0000.0000.0000.0000.0080.0070.0140.0000.0000.0030.0000.3220.005
Response Type_Collar0.0000.0000.0510.0000.0000.0170.0380.0470.0000.0060.0420.0270.0250.0000.0000.0460.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0030.0000.0000.0000.0000.0000.0110.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0550.0000.0000.0000.0000.0000.0000.0000.0000.0000.0480.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0050.0000.0000.0040.0000.0040.0000.0000.0000.0000.0000.0000.0000.0000.0100.0001.0000.0000.0000.0000.0000.0000.0000.0000.0730.0000.0370.0000.0050.1170.0000.0000.0030.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0160.0000.0070.000
Response Type_Collect Sample0.1960.2040.0000.0000.0000.4230.4230.1940.0120.2340.3400.1590.1340.0990.1860.0930.0060.0130.0000.0000.0240.0000.0010.0210.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0060.0000.0050.0000.0000.0050.0000.0000.0000.0000.0100.0000.0000.0000.0050.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.1220.0000.0000.0000.0000.0000.0000.0000.0000.0040.0230.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0120.0060.0000.0000.0000.0000.0000.0230.0000.0000.0160.0000.0270.0000.0000.0320.0040.0000.0000.0000.2310.2190.5080.0001.0000.5290.0090.0000.0000.0180.0620.0000.0260.0000.0140.0630.0000.1190.0020.0300.0000.0000.0000.0250.0000.3780.0300.0070.4260.0030.0000.0260.0000.0150.0150.0000.0100.0000.0080.0060.1760.012
Response Type_Cull0.3610.3490.0000.0000.0000.7440.7440.3050.0000.1380.6130.0960.0120.0000.3111.0000.0000.0000.0000.0000.0000.0000.0000.0130.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0350.0000.0000.0000.0000.0000.0000.0050.0000.0000.0000.0000.0000.0130.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.2010.0000.0000.0000.0000.0000.0000.0000.0000.0090.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0080.0000.0000.0000.0000.0000.0000.0220.0000.0000.0000.0000.0140.0000.0000.0000.0000.0000.0000.0000.3970.4040.9320.0000.5291.0000.0010.0000.0000.0090.0120.0000.0000.0000.0080.0350.0000.2320.0000.0300.0000.0000.0000.0030.0000.6880.0200.0100.6340.0000.0000.0000.0000.0080.0000.0000.0070.0000.0050.0000.3380.008
Response Type_Destroy Animal0.0340.1160.0590.0000.0220.1350.1490.1580.0200.2290.4320.1060.1470.0980.7490.0610.0070.0040.0000.0000.0300.0000.0000.0250.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0160.0000.0000.0090.0000.0000.0000.0000.0000.0070.0130.0000.0050.0000.0000.0030.0080.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0210.0000.0000.0000.0000.0000.0000.0000.0000.0320.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0150.0000.0000.0100.0000.0000.0000.0140.0080.0000.0140.0000.0000.0070.0000.0020.0000.0000.0120.0020.0000.0320.0000.0090.0060.0000.0000.0090.0011.0000.0000.0040.0220.0840.0480.0050.0000.0200.0690.0240.0030.0040.0110.0000.0000.0000.0110.0000.0030.0020.0190.0890.0040.0050.0000.0070.0000.0070.0070.0020.0000.0270.0080.0000.010
Response Type_Disentangle0.0140.0460.0170.0000.0000.0600.1180.0670.0000.0530.1620.1080.0640.0300.0900.0000.0000.0000.0000.0000.0030.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0100.0000.0170.0000.0000.0000.0000.0040.0060.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0370.0000.0000.0140.0000.0000.0000.0000.0000.0000.0000.0000.0080.0340.0320.0000.0000.0000.0000.0000.0000.0000.0000.0240.0000.0000.0000.0000.0000.0130.0000.0000.0000.0000.0070.0000.0030.0050.0000.0000.0000.0120.0000.0000.0030.0000.0160.0000.0000.0000.0010.0000.0000.0000.0000.0001.0000.0000.0010.0030.0000.0020.0000.0120.0230.0430.0000.0000.0230.0000.0000.0000.0000.0000.0000.0080.0070.0000.0000.0000.0000.0240.0000.0000.0000.0000.0000.0000.0000.0000.006
Response Type_Dispatch other Agency0.0130.0370.0070.0000.0000.0320.0560.0940.0790.0360.0250.0370.0630.1360.0250.0450.0000.0070.0050.0000.0030.0000.0000.0090.0000.0000.0000.0000.0000.0000.0000.0000.0220.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0040.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0050.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0330.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0080.0000.0000.0000.0000.0070.0000.0260.0420.0000.0000.0000.0130.0080.0000.0050.0000.0000.0000.0040.0001.0000.0070.0000.0000.0000.0090.0050.0260.0000.0030.0000.0000.0000.0000.0000.0020.0000.0000.0000.0000.0000.0000.0070.0020.0000.0070.0140.0050.0000.0000.0040.0000.0000.002
Response Type_Disperse Wildlife Jam0.0510.0490.0180.0000.0000.2300.1190.1220.0180.1110.0680.1560.1280.2210.1640.0650.0170.0180.0000.0000.0020.0000.0210.0550.0100.0000.0000.0000.0000.0000.0000.0000.0060.0070.0100.0020.0010.0180.0000.0160.2560.0020.0000.0000.0000.0000.0000.0320.0000.0050.0000.0100.0050.0520.0080.0000.0000.0000.0000.0000.0000.0000.0000.0160.0000.0000.0430.0000.0000.0000.0000.0170.0000.0000.0000.0450.0040.0010.0000.0000.0050.0000.0000.0040.0000.0020.0000.0000.0000.0000.0000.0000.0430.0000.0000.0000.0000.0000.0000.0890.0000.0000.0060.0000.0380.0000.0090.0080.0000.0080.0350.0000.0260.0170.0090.0000.0180.0090.0220.0010.0071.0000.0570.0070.0140.0030.0170.0240.0050.0230.0120.1040.0000.0050.0000.0250.0050.0120.0000.0350.0160.0130.0140.0180.0000.0400.0100.0130.0910.0000.0320.0160.0190.035
Response Type_Dispose Carcass0.0630.1240.0370.0300.0000.1600.1850.4730.0030.6560.4430.3060.2470.3380.3960.1830.0220.0160.0000.0000.0000.0000.0160.0620.0120.0000.0000.0000.0000.0000.0000.0000.0930.0030.0120.0130.0000.0100.0000.0050.1380.0040.0000.0000.0000.0000.0000.0220.0000.0080.0070.0160.0190.0350.0000.0000.0000.0000.0000.0010.0000.0000.0000.0030.0000.0000.0140.0000.0000.0000.0000.0170.0020.0000.0000.0880.0000.0000.0000.0040.0050.0000.0000.0070.0000.0000.0000.0000.0000.0000.0000.0000.0290.0000.0000.0000.0000.0000.0000.0770.0000.0000.0000.0000.0160.0000.0000.0040.0000.0060.0110.0000.0300.0000.0080.0000.0620.0120.0840.0030.0000.0571.0000.0000.0220.0050.0530.1840.0080.0290.0160.0620.0000.0080.0000.0120.0040.0080.0820.0600.0640.0150.0110.0050.0000.0170.0250.0000.0250.0030.0300.0220.0200.042
Response Type_Ear Tag0.0000.0660.0300.0000.0000.0810.0980.0130.0040.0300.0550.0920.0680.0960.0950.0710.0000.0000.0000.0000.0000.0000.0000.0260.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0410.0000.0050.0210.0000.0000.0000.0000.0000.0000.0050.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0050.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0130.0000.0000.0000.0000.0000.0000.0000.0080.0000.0000.0000.0000.0020.0020.0000.0730.0000.0000.0480.0000.0000.0070.0001.0000.0000.0080.0000.0000.1230.0220.0000.0200.0000.0000.0000.0000.0000.0000.0230.0090.0000.0000.0000.0020.0000.0220.0140.0000.0040.0000.0880.0000.0710.051
Response Type_Euthanize0.0310.0440.0440.0000.0000.0600.0610.1190.0150.1790.1250.1570.2130.0900.4860.1190.0030.0160.0000.0000.0000.0000.0050.0110.0000.0000.0000.0000.0000.0000.0000.0000.0310.0000.0000.0000.0000.0000.0000.0000.0160.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0010.0070.0000.0000.0000.0000.0000.0000.0270.0110.0000.0050.0000.0000.0130.0000.0000.0000.0000.0000.0000.0000.0000.0360.0060.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0020.0000.0140.0000.0000.0060.0000.0200.0000.0000.0150.0070.0010.0000.0000.0020.0060.0000.0000.0260.0000.0050.0020.0000.0140.0220.0001.0000.0000.0130.0470.0090.0070.0000.0350.0000.0000.0000.0290.0000.0000.0220.0090.0090.0000.0000.0000.0000.0060.0000.0000.0070.0000.0060.0030.0000.012
Response Type_Evacuate Visitor0.0200.0330.0720.0000.0000.0500.0550.0230.0000.0370.0600.0750.0690.0400.0460.1150.0000.0160.0000.0000.0000.0000.0210.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0200.0030.0000.0130.0000.0000.0140.0000.0040.0000.0000.0000.0000.0000.0000.0130.0000.0070.0070.0420.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0050.0010.0000.0000.0000.0130.0000.0000.0030.0000.0000.0000.0000.0000.0130.0000.0000.0030.0000.0000.0000.0000.0000.0000.0150.0000.0000.0000.0000.0000.0000.0290.0250.0130.0120.0090.0260.0000.0620.0070.0370.0000.0000.0000.0000.0090.0030.0050.0080.0001.0000.0000.0180.0110.0470.0000.0000.0000.0130.0000.0000.0000.0180.0150.0170.0000.0000.0000.0000.0000.0000.0110.0000.0040.0000.0000.0000.0360.000
Response Type_Haze - Hard0.0590.0640.0200.0170.0000.0840.0860.1250.0180.1050.0850.1150.1320.1220.5100.1960.0140.0090.0000.0000.0010.0000.0190.0050.0000.0000.0000.0000.0000.0000.0000.0000.0070.0000.0090.0000.0000.0070.0000.0080.0320.0000.0030.0000.0000.0000.0000.0450.0000.0000.0020.0000.0110.0320.0000.0000.0000.0000.0000.0000.0000.0000.0000.0030.0000.0000.0150.0000.0000.0000.0000.0070.0000.0000.0000.0360.0040.0000.0000.0000.0000.0000.0000.0030.0000.0000.0000.0000.0000.0000.0000.0040.0000.0000.0000.0000.0000.0000.0000.0950.0000.0000.0020.0000.0600.0000.0090.0090.0000.0030.0050.0030.0200.0130.0080.0000.0140.0080.0200.0120.0050.0170.0530.0000.0130.0001.0000.1260.0000.0220.0110.1110.0000.0000.0000.0230.0000.0110.0440.0340.0140.0120.0130.0170.0000.0350.0100.0090.0080.0000.0250.0170.0140.037
Response Type_Haze - Soft0.1340.2090.0280.0100.0000.2680.2480.4020.0640.4680.2780.2560.3620.4080.6380.5920.0510.0430.0100.0040.0180.0000.0620.0030.0290.0020.0150.0060.0000.0000.0000.0000.0310.0010.0230.0100.0000.0380.0000.0390.0920.0340.0140.0000.0000.0020.0000.0680.0100.0000.0110.0000.0230.1020.0160.0060.0000.0040.0090.0000.0000.0020.0000.0370.0000.0000.0000.0000.0000.0000.0020.0190.0070.0000.0030.0390.0220.0160.0000.0050.0150.0000.0000.0150.0100.0140.0000.0000.0000.0060.0000.0000.0000.0040.0000.0000.0070.0060.0000.2320.0050.0000.0280.0000.0080.0000.0320.0380.0030.0350.0060.0200.0830.0630.0350.0050.0630.0350.0690.0230.0260.0240.1840.0000.0470.0180.1261.0000.0100.0660.0440.3460.0140.0200.0000.0830.0130.0410.1560.1360.0500.0450.0460.0600.0080.1280.0300.0000.0310.0150.0910.0610.0640.097
Response Type_Immobilize Animal0.0110.0330.1200.0000.0000.0630.0660.0380.0140.0360.0740.0450.0360.0310.0750.0390.0000.0000.0000.0000.0000.0000.0000.0070.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0030.0000.0000.0000.0070.0220.0000.0040.0000.0000.0000.0000.0000.0070.0000.0000.0000.0000.0060.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0100.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0080.0000.0000.0000.0000.0160.0000.0000.0100.0000.0000.0000.0150.0000.0000.0000.1170.0000.0000.0240.0430.0000.0050.0080.1230.0090.0110.0000.0101.0000.0090.0000.0000.0000.0000.0000.0000.0000.0000.0000.0080.0010.0000.0000.0000.0070.0200.0000.0000.0000.0000.0360.0000.0070.000
Response Type_Inform Visitor0.1510.1960.0500.0390.0060.2660.2720.1850.0090.0430.3990.1420.0800.1260.1140.1050.0110.0460.0000.0000.0000.0000.0430.0510.0080.0000.0030.0000.0000.0000.0000.0000.0080.0090.0020.0040.0000.0330.0000.0200.0620.0060.0000.0080.0000.0100.0000.0280.0100.0000.0320.0010.0710.0670.0000.0000.0000.0000.0130.0000.0000.0000.0000.0080.0000.0030.0500.0000.0000.0000.0000.0270.0000.0000.0090.0370.0040.0000.0000.0000.0000.0000.0000.0000.0000.0010.0000.0000.0000.0000.0080.0000.0300.0080.0000.0000.0000.0000.0000.0500.0000.0000.0000.0000.0250.0000.0250.0170.0000.0310.0280.0000.1040.1210.2320.0000.1190.2320.0030.0000.0030.0230.0290.0220.0070.0470.0220.0660.0091.0000.0120.0130.0000.0040.0000.0190.0000.1750.1170.0320.1640.0080.0180.0000.0000.0180.0290.0620.0530.0000.0000.0140.1870.004
Response Type_Infrastructure modification0.0710.1860.0740.0000.0000.3190.4280.3740.0040.0000.0260.0550.0500.0670.0001.0000.0010.0030.0000.0000.0000.0000.0030.0170.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0020.0000.0000.0020.0000.0000.0000.0000.0000.0000.0080.0000.0000.0000.0000.0030.0020.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.1200.0000.0000.0000.0000.0020.0000.0000.0000.0120.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0090.0000.0000.0000.0000.0000.0000.0280.0000.0000.0000.0000.0180.0000.0000.0000.0000.0000.0000.0000.0050.0030.0000.0000.0020.0000.0040.0000.0000.0120.0160.0000.0000.0000.0110.0440.0000.0121.0000.0380.0000.0000.0000.0050.0000.0000.0250.0130.0000.0000.0000.0020.0000.0100.0000.0000.0090.0000.0070.0020.0070.010
Response Type_Investigate Incident0.0530.0340.0270.0140.0040.1300.1330.1790.0210.3180.1820.1750.1880.2510.2980.4030.0050.0090.0000.0000.0000.0000.0400.0470.0110.0000.0040.0030.0000.0000.0000.0040.0130.0000.0290.0100.0000.0430.0000.0120.0520.0180.0040.0000.0000.0020.0000.0140.0080.0100.0020.0000.0050.0680.0160.0070.0000.0090.0050.0000.0000.0020.0000.0000.0000.0000.0200.0000.0000.0000.0000.0030.0060.0000.0050.0110.0000.0110.0030.0000.0180.0000.0000.0100.0000.0120.0000.0000.0000.0000.0000.0000.0190.0000.0000.0000.0000.0000.0000.1100.0000.0040.0000.0000.1050.0000.0000.0130.0000.0140.0080.0000.0490.0270.0270.0030.0300.0300.0110.0230.0000.1040.0620.0200.0350.0000.1110.3460.0000.0130.0381.0000.0070.0130.0000.0470.0180.0240.0250.0890.0100.0340.0000.0000.0050.0710.0250.0370.0660.0120.0480.0500.0160.047
Response Type_Issue Prohibited Activity Order0.0000.0000.0300.0000.0000.0330.0270.0880.0000.0000.0000.0220.0000.0240.0001.0000.0000.0000.0000.0000.0000.0000.0000.0040.0000.0000.0000.0000.0620.0000.0000.0000.0000.0000.0000.0000.0000.0080.0000.0000.0050.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0170.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0060.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0140.0000.0000.0000.0071.0000.0000.0000.0000.0000.0000.0020.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0070.0000.0010.000
Response Type_Issue Restricted Activity Order0.0200.0000.0560.0000.0000.0340.0380.1030.0050.0030.0000.0420.0250.0000.0000.0470.0000.0000.0000.0000.0000.0000.0060.0000.0000.0130.0000.0000.0000.0000.0000.0000.0000.0000.0000.0050.0000.0070.0000.0000.0100.0000.0000.0000.0000.0000.0000.0010.0000.0000.0190.0000.0000.0350.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0050.0040.0000.0000.0000.0030.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0130.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0070.0000.0000.0000.0000.0000.0000.0000.0050.0080.0000.0000.0130.0000.0200.0000.0040.0000.0130.0001.0000.0000.0000.0000.0000.0000.0060.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0220.000
Response Type_Issue Stop Work Order0.0000.0000.0000.0000.0000.0060.0000.0000.0001.0001.0000.0001.0000.0001.0001.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0130.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0220.0000.0000.0000.0000.0000.0000.0130.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0001.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0030.0000.0000.0000.0000.0000.0000.0000.000
Response Type_Leave on Landscape0.0820.0910.0220.0000.0410.2060.2150.2170.0230.2780.1610.2760.2320.2020.1820.1470.0030.0270.0000.0120.0000.0000.0070.0270.0060.0000.0290.0000.0000.0000.0000.0000.0000.0000.0030.0000.0000.0000.0000.0080.0630.0050.0000.0000.0000.0000.0000.0140.0180.0000.0020.0000.0040.0090.0020.0190.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0140.0050.0050.0000.0000.0000.0000.0000.0040.0090.0160.0000.0000.0000.0000.0150.0000.0140.0000.0000.0000.0410.0000.0130.0000.0000.0120.0000.0000.0000.0120.0000.0000.0430.0000.0000.0130.0000.0360.0000.0000.0010.0000.0000.0020.0000.0920.0240.0030.0000.0250.0030.0110.0000.0020.0250.0120.0000.0290.0000.0230.0830.0000.0190.0050.0470.0000.0000.0001.0000.0000.0050.0380.0140.0000.0050.0010.0100.0000.0180.0000.0040.0150.0000.0160.0090.0030.022
Response Type_Mark - paint0.0000.0580.0080.0000.0000.0760.0750.0210.0000.0130.0000.0990.0820.0310.3250.0280.0000.0000.0000.0000.0000.0000.0000.0070.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0260.0000.0000.0130.0000.0000.0000.0000.0000.0000.0010.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0130.0000.0000.0000.0050.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0030.0000.0000.0000.0000.0100.0000.0340.0000.0000.0000.0000.0090.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0050.0040.0000.0000.0000.0000.0130.0000.0000.0000.0180.0000.0000.0000.0001.0000.0000.0000.0040.0000.0000.0000.0000.0000.0000.0000.0000.0030.0000.0000.0000.0000.004
Response Type_Monitor - Camera0.2580.2450.1200.1180.0000.5250.5270.2290.0000.1060.5700.0930.0900.0880.1440.0360.0000.0000.0000.0000.0000.0000.0470.0120.0120.0040.0000.0000.0000.0000.0000.0000.0070.0000.0000.0000.0000.0260.0000.0020.0410.0000.0000.0000.0000.0000.0000.0090.0000.0000.0000.0020.0000.0220.0000.0000.0000.0000.0000.0000.0000.0000.0000.0050.0000.0000.1470.0000.0000.0000.0000.0000.0000.0000.0000.0140.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0080.0000.0000.0000.0000.0000.0000.0180.0000.0000.0000.0000.0210.0000.0000.0050.0000.0300.0000.0000.2800.3330.6540.0000.3780.6880.0030.0000.0000.0120.0080.0000.0000.0180.0110.0410.0000.1750.0000.0240.0000.0000.0000.0050.0001.0000.0160.0150.4510.0000.0000.0000.0240.0120.0000.0000.0080.0000.0020.0030.2800.012
Response Type_Monitor - patrol0.1760.1450.0550.0210.0110.2320.2370.1690.0000.1760.1740.2100.0780.1120.2390.2300.0120.0250.0000.0000.0100.0000.0000.0160.0080.0000.0000.0000.0000.0050.0000.0000.0090.0000.0050.0260.0000.0000.0000.0000.0350.0110.0090.0000.0120.0120.0000.0340.0040.0110.0000.0020.0140.0540.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0260.0000.0000.0000.0000.0120.0000.0000.0000.0570.0000.0050.0000.0060.0020.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0370.0000.0000.0000.0010.0020.0000.0900.0000.0000.0000.0000.0860.0000.0040.0060.0060.0050.0180.0020.0340.0060.0140.0000.0300.0200.0020.0080.0000.0000.0820.0230.0220.0150.0440.1560.0000.1170.0250.0250.0020.0000.0000.0380.0000.0161.0000.0190.0000.0250.0010.0080.0000.0510.0170.0310.0400.0030.0150.0340.0700.011
Response Type_Monitor - visitor and staff sighting0.1030.4610.0280.0000.0000.4750.4760.3100.0340.2810.2030.1550.2090.1210.2380.2650.2810.0780.0200.0030.0060.0000.1240.0110.0030.0000.0000.0000.0000.0000.0000.0000.0060.0000.0000.0000.0000.0000.0000.0160.0200.0060.0160.0000.0000.0000.0000.0300.0000.0000.0100.0000.0000.1030.0000.0000.0000.0080.0000.0000.0000.0000.0000.0380.0000.0000.0470.0000.0000.0000.0160.0120.0000.0000.0000.0470.0040.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0360.0260.0000.0000.0000.0000.0000.0640.0000.0000.0170.0000.0710.0000.0080.0000.0000.0120.0020.0050.0250.0120.0080.0000.0070.0100.0190.0070.0000.0350.0600.0090.0090.0170.0340.1360.0080.0320.0130.0890.0000.0060.0000.0140.0040.0150.0191.0000.0120.0070.0140.0000.0000.0390.0030.0100.0180.0000.0310.0080.0190.044
Response Type_Necropsy0.2510.2380.0240.0000.0000.5050.5060.2110.0120.1940.4790.0960.1440.0930.3250.0160.0000.0350.0110.0000.0290.0000.0000.0130.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0010.0000.0040.0000.0030.0320.0000.0000.0000.0000.0000.0000.0030.0000.0000.0000.0030.0000.0050.0000.0000.0000.0000.0000.0000.0000.0000.0000.0060.0240.0000.1480.0000.0000.0170.0000.0040.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0160.0000.0000.0000.0000.0060.0000.0000.0140.0080.0000.0000.0000.0000.0000.0240.0000.0000.0250.0000.0000.0000.0000.0180.0000.0000.0000.0050.2590.2600.6020.0000.4260.6340.0890.0000.0000.0160.0640.0000.0090.0000.0140.0500.0010.1640.0000.0100.0000.0000.0000.0000.0000.4510.0000.0121.0000.0000.0010.0100.0000.0060.0140.0000.0100.0000.0000.0040.2230.000
Response Type_No response required0.0370.0660.0070.0000.0000.1110.1320.0290.0060.0150.0000.0510.0910.1120.0990.0300.0000.0000.0000.0000.0000.0000.0040.0160.0070.0000.0000.0000.0000.0000.0000.0000.0000.0100.0110.0000.0000.0020.0000.0000.0060.0000.0000.0000.0000.0000.0000.0080.0000.0000.0120.0000.0000.0350.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0030.0000.0000.0000.0000.0000.0000.0000.0000.0040.0000.0000.0100.0000.0000.0000.0000.0000.0050.0000.0000.0000.0000.0000.0000.0000.0030.0000.0000.0000.0000.0030.0000.0210.0000.0000.0000.0000.0190.0000.0000.0000.0000.0000.0000.0000.0060.0060.0000.0000.0030.0000.0040.0000.0000.0130.0150.0000.0000.0000.0120.0450.0000.0080.0000.0340.0000.0000.0000.0050.0000.0000.0250.0070.0001.0000.0000.0000.0000.0110.0000.0000.0100.0000.0080.0000.0060.011
Response Type_Not Applicable0.0930.1050.0390.0000.0000.1270.1700.0480.0280.0380.0670.0640.0690.0670.0480.0270.0040.0000.0000.0000.0000.0000.0200.0100.0090.0000.0000.0000.0000.0000.0000.0000.0000.0030.0000.0000.0000.0000.0000.0140.0150.0000.0000.0000.0000.0000.0000.0090.0000.0050.0000.0000.0000.0320.0000.0000.0000.0000.0000.0000.0000.0000.0000.0220.0000.0000.0230.0000.0000.0000.0000.0030.0000.0000.0000.0090.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0070.0000.0000.0000.0000.0000.0000.0180.0000.0000.0290.0000.0000.0000.0110.0530.0000.0010.0000.0000.0040.0030.0000.0000.0000.0000.0050.0000.0070.0140.0110.0000.0000.0000.0130.0460.0000.0180.0000.0000.0000.0000.0000.0010.0000.0000.0010.0140.0010.0001.0000.0000.0000.0090.0540.0620.0000.0000.0000.0030.0220.032
Response Type_Refer incident to other agency0.0220.0920.0000.0000.0110.0960.0950.1570.1600.0650.0850.0930.0950.1590.0660.0760.0000.0540.0230.0000.0050.0140.0060.0070.0000.0000.0000.0000.0000.0000.0000.0000.0140.0000.0000.0000.0000.0110.0000.0270.0160.0000.0000.0000.0000.0000.0000.0060.0000.0000.0160.0010.0040.0000.0000.0000.0000.0030.0140.0000.0000.0000.0000.0090.0000.0000.0000.0000.0000.0000.0080.0000.0000.0000.0000.0260.0000.0000.0000.0000.0000.0000.0000.0000.0000.0190.0000.0000.0000.0000.0000.0000.0000.0220.0000.0000.0000.0000.0000.0080.0000.0000.0190.0000.0000.0000.0000.0630.0000.0140.0000.0000.0170.0040.0000.0000.0260.0000.0000.0000.0020.0180.0050.0020.0000.0000.0170.0600.0000.0000.0020.0000.0000.0000.0000.0100.0000.0000.0080.0000.0100.0000.0001.0000.0000.0150.0070.0000.0110.0000.0000.0000.0090.014
Response Type_Rehabilitate area0.0230.1430.0200.0000.0000.1000.1420.0560.0080.0190.0000.0230.0000.0000.0520.0000.0000.0090.0000.0000.0130.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0050.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0120.0000.0000.0150.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0050.0000.0030.0000.0000.0000.0000.0410.0230.0000.0050.0000.0000.0000.0000.0000.0070.0240.0000.0000.0000.0000.0000.0000.0000.0080.0070.0000.0000.0050.0000.0000.0000.0000.0000.0240.0000.0000.0000.0000.0000.0001.0000.0000.0000.0000.0000.0000.0090.0000.0000.000
Response Type_Relocate animal (s)0.3140.3070.1010.0000.0000.3380.3860.1680.0000.1110.1950.2070.3930.1950.1450.1640.0150.0000.0000.0000.0000.0000.0170.0130.0970.0000.0000.0000.0000.0000.0000.0000.0070.0080.0000.0080.0000.0040.0000.0520.1030.0030.0000.0000.0000.0000.0000.0200.0000.0070.0070.0000.0080.0150.0000.0000.0000.0000.0000.0000.0000.0000.0000.0580.0000.0000.0120.0000.0000.0000.0000.0040.0130.0000.0000.0200.0000.0000.0000.0090.0050.0000.0000.0000.0000.0050.0000.0000.0000.0000.0000.0050.0740.0000.0000.0090.0000.0000.0000.0000.0140.0000.0050.0000.0880.0000.0000.0030.0000.0070.0000.0000.0200.0110.0080.0000.0150.0080.0000.0000.0070.0400.0170.0220.0060.0000.0350.1280.0200.0180.0100.0710.0000.0000.0030.0180.0000.0120.0510.0390.0060.0110.0090.0150.0001.0000.0000.0000.0240.0000.3380.0150.0090.020
Response Type_Request assistance - other Agency0.0330.0500.0180.0000.0000.0560.0640.1300.0480.0600.0000.0680.0480.1390.0250.0850.0010.0150.0010.0000.0000.0000.0000.0120.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0050.0000.0170.0140.0000.0000.0000.0000.0000.0000.0060.0000.0000.0000.0000.0000.0050.0000.0060.0000.0000.0000.0000.0000.0000.0000.0140.0000.0000.0040.0000.0130.0000.0000.0000.0000.0000.0000.0550.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0100.0000.0000.0000.0000.0000.0150.0000.0000.0000.0000.0130.0000.0090.0840.0000.0050.0000.0310.0140.0000.0070.0000.0150.0000.0070.0000.0140.0100.0250.0140.0000.0110.0100.0300.0000.0290.0000.0250.0000.0000.0000.0000.0000.0000.0170.0030.0140.0000.0540.0070.0000.0001.0000.0860.0000.0000.0000.0000.0350.015
Response Type_Request assistance - police0.0370.0460.0760.0000.0000.0570.0590.0940.0210.0290.0940.0690.0600.0790.0420.0670.0000.0060.0030.0000.0000.0000.0000.0000.0000.0000.0020.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0020.0000.0000.0000.0000.0000.0000.0000.0040.0000.0000.0000.0000.0000.0020.0000.0080.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0110.0000.0000.0000.0000.0000.0000.0000.0000.0080.0000.0140.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0150.0000.0000.0000.0000.0310.0000.0110.0720.0000.0000.0000.0100.0000.0220.0140.0000.0000.0000.0070.0000.0050.0130.0000.0000.0000.0000.0090.0000.0000.0620.0000.0370.0000.0000.0000.0040.0000.0000.0310.0100.0000.0000.0620.0000.0000.0000.0861.0000.0600.0000.0040.0000.0430.037
Response Type_Traffic control0.0760.0410.0220.0000.0000.1840.1180.0920.0110.0670.1030.1020.1010.1680.1060.0270.0140.0080.0000.0000.0000.0000.0170.0460.0070.0000.0000.0000.0000.0000.0000.0000.0060.0000.0040.0000.0000.0130.0000.0120.1810.0000.0000.0000.0040.0000.0000.0250.0000.0030.0000.0080.0180.0370.0060.0000.0000.0000.0000.0000.0000.0000.0000.0080.0000.0000.0230.0000.0000.0000.0000.0070.0000.0000.0000.0360.0020.0000.0000.0000.0030.0000.0000.0000.0000.0000.0000.0000.0000.0000.0040.0000.0280.0000.0000.0000.0000.0000.0000.0730.0000.0000.0020.0000.0120.0000.0000.0030.0000.0040.0000.0020.0110.0000.0000.0000.0100.0070.0020.0000.0000.0910.0250.0040.0070.0040.0080.0310.0000.0530.0090.0660.0000.0000.0000.0150.0030.0080.0400.0180.0100.0100.0000.0110.0000.0240.0000.0601.0000.0000.0230.0140.0000.025
Response Type_Translocate0.0060.0140.0000.0000.0000.0210.0180.1470.0000.0270.0440.0220.0620.0330.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0180.0150.0000.0000.0000.0000.0000.0000.0000.0150.0000.0000.0000.0000.0040.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0090.0000.0000.0000.0000.0000.0000.0000.0000.0000.0080.0000.0000.0000.0000.0000.0000.0000.0000.0110.0000.0000.0000.0000.0000.0000.0330.0000.0000.0000.0000.0000.0000.0000.0000.0000.0040.0000.0040.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0030.0000.0000.0000.0000.0150.0000.0000.0000.0120.0000.0000.0000.0000.0000.0000.0030.0000.0000.0000.0000.0000.0000.0000.0000.0000.0001.0000.0770.0000.0000.000
Response Type_Trap or snare0.2970.2720.0610.0180.0000.3120.3630.3410.0050.0580.3180.1510.1640.1810.1100.0520.0110.0090.0000.0000.0160.0000.0070.0060.0000.0060.0000.0000.0000.0000.0000.0000.0040.0030.0060.0070.0000.0090.0000.1350.1020.0030.0000.0000.0000.0000.0000.0190.0000.0000.0050.0100.0110.0350.0040.0000.0000.0000.0000.0000.0000.0000.0000.0200.0000.0000.0220.0000.0000.0000.0030.0000.0000.0000.0000.0300.0210.0000.0000.0000.0000.0000.0000.0000.0000.0090.0210.0000.0000.0000.0000.0000.0700.0000.0000.0000.0000.0000.0000.0130.0240.0070.0010.0000.1370.0050.0000.0040.0000.0030.0000.0180.0160.0160.0030.0160.0080.0050.0270.0000.0040.0320.0300.0880.0060.0000.0250.0910.0360.0000.0070.0480.0070.0000.0000.0160.0000.0020.0150.0310.0000.0080.0000.0000.0090.3380.0000.0040.0230.0771.0000.0120.0310.023
Response Type_Unable to respond0.0560.0350.0140.0000.0000.0600.0470.0470.0050.0300.0000.0710.0300.0360.0690.0740.0020.0040.0000.0040.0000.0000.0000.0090.0020.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0040.0520.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0030.0020.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0150.0000.0000.0000.0000.0090.0000.0080.0000.0150.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0030.0000.0000.0300.0150.0000.0000.0000.0260.0000.0010.0030.0000.0040.0000.0000.0050.0090.0000.0000.0060.0000.0080.0000.0000.0160.0220.0000.0030.0000.0170.0610.0000.0140.0020.0500.0000.0000.0000.0090.0000.0030.0340.0080.0040.0000.0030.0000.0000.0150.0000.0000.0140.0000.0121.0000.0110.016
Response Type_Warning signs0.1800.1670.1350.0570.0160.2910.3090.2530.0130.0630.4830.1720.1260.1600.1670.1390.0150.0120.0000.0000.0240.0000.0750.0310.0090.0000.0060.0140.0080.0060.0000.0000.0000.0170.0100.0000.0000.0370.0270.0000.0720.0020.0160.0120.0000.0000.0000.0160.0130.0000.0000.0000.0050.0980.0000.0000.0000.0000.0140.0000.0000.0000.0000.0080.0000.0080.0840.0000.0000.0000.0000.0240.0000.0000.0000.0280.0000.0000.0000.0000.0110.0000.0000.0060.0000.0000.0000.0000.0000.0000.0070.0000.0190.0000.0000.0000.0000.0000.0000.0360.0000.0000.0050.0000.0140.0000.0180.0270.0000.0180.0000.0000.1320.2120.3220.0070.1760.3380.0000.0000.0000.0190.0200.0710.0000.0360.0140.0640.0070.1870.0070.0160.0010.0220.0000.0030.0000.2800.0700.0190.2230.0060.0220.0090.0000.0090.0350.0430.0000.0000.0310.0111.0000.054
Response Type_nan0.0610.0640.0620.0330.0180.1040.1120.1030.0170.1260.0660.0630.0770.1200.1611.0000.0120.0000.0030.0000.0000.0000.0000.0020.0000.0000.0000.0000.0000.0000.0000.0000.0070.0030.0000.0050.0000.0020.0000.0170.0340.0050.0000.0000.0000.0000.0000.0140.0000.0000.0050.0110.0060.0070.0080.0000.0000.0000.0000.0000.0000.0000.0000.0050.0000.0000.0210.0000.0000.0000.0000.0010.0000.0000.0000.0060.0060.0000.0000.0000.0000.0000.0000.0020.0020.0120.0000.0000.0000.0000.0000.0000.0180.0000.0000.0000.0000.0000.0210.0340.0000.0000.0000.0000.1120.0000.0000.0230.0000.0130.0070.0000.0220.0220.0050.0000.0120.0080.0100.0060.0020.0350.0420.0510.0120.0000.0370.0970.0000.0040.0100.0470.0000.0000.0000.0220.0040.0120.0110.0440.0000.0110.0320.0140.0000.0200.0150.0370.0250.0000.0230.0160.0541.000

Missing values

2023-03-18T21:17:08.757594image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-03-18T21:17:11.505598image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.
2023-03-18T21:17:24.222674image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

Sample

UniqueIDIncident NumberIncident DateField UnitProtected Heritage AreaIncident TypeLatitude PublicLongitude PublicWithin ParkTotal Staff InvolvedTotal Staff HoursSpecies Common NameSum of Number of AnimalsAnimal Health StatusCause of Animal Health StatusAnimal BehaviourReason for Animal BehaviourAnimal AttractantDeterrents UsedAnimal Response to DeterrentsActivity Type_Backpacking – Multiday TripsActivity Type_Beach RecreationActivity Type_Boating - Coastal/MarineActivity Type_Boating - CommercialActivity Type_Boating - Motorized Pleasure CraftActivity Type_Bush PartyActivity Type_Camping - BackcountryActivity Type_Camping - FrontcountryActivity Type_Camping - Huts and LodgesActivity Type_Camping - Winter FrontcountryActivity Type_Canoeing - FlatwaterActivity Type_Canoeing - SwiftwaterActivity Type_CanyoneeringActivity Type_Climbing - MountaineeringActivity Type_Climbing - Technical RockActivity Type_Climbing - Waterfall IceActivity Type_Commercial Transportation OperationActivity Type_CyclingActivity Type_Cycling - Mountain BikingActivity Type_Cycling - Road/Shared PathActivity Type_Cycling - WinterActivity Type_Dog WalkingActivity Type_DogsleddingActivity Type_Domestic Residence ActivityActivity Type_DrivingActivity Type_Field SportsActivity Type_FishingActivity Type_Flight - HETSActivity Type_Flight - Hang-gliding/ParapentingActivity Type_Flight - HelicopterActivity Type_Flight - Sightseeing/Site AccessActivity Type_GolfingActivity Type_Heritage Activity - Bird WatchingActivity Type_Heritage Activity - History ActivitiesActivity Type_Heritage Activity - Photography and ArtActivity Type_Heritage Activity - SightseeingActivity Type_Heritage Activity - Wildlife ObservationActivity Type_Hiking / WalkingActivity Type_Horse Riding - Day TripActivity Type_Horse Riding - MultidayActivity Type_Ice SkatingActivity Type_Kayaking - CoastalActivity Type_Kayaking - FlatwaterActivity Type_Kayaking - SwiftwaterActivity Type_MooringActivity Type_Not ApplicableActivity Type_Orienteering / GeocachingActivity Type_OtherActivity Type_Paddleboarding - CoastalActivity Type_Paddleboarding - FlatwaterActivity Type_Park OperationsActivity Type_Park Ops - Avalanche ForecastingActivity Type_Park Ops - Avalanche ControlActivity Type_Park Ops - Search and RescueActivity Type_Park Ops - TrainingActivity Type_Picnicking / BBQActivity Type_Playground ActivitiesActivity Type_Rafting - FlatwaterActivity Type_Rafting - SwiftwaterActivity Type_RailwayActivity Type_Research - Scientific/SocialActivity Type_Resource Harvesting - Hunting/Fishing/Gathering/TrappingActivity Type_Roller SportsActivity Type_Running - RoadActivity Type_Running - TrailActivity Type_Sail Sports - Wind / Kite SurfingActivity Type_ScramblingActivity Type_Skiing - CrosscountryActivity Type_Skiing/Boarding - BackcountryActivity Type_Skiing/Boarding - Ski Resort In BoundsActivity Type_Skiing/Boarding - Ski Resort Out of BoundsActivity Type_Sledding/TobogganningActivity Type_SnowmobilingActivity Type_SnowshoeingActivity Type_Special Event - Participative AudienceActivity Type_Special Events - Passive AudienceActivity Type_Stakeholder OperationsActivity Type_SurfingActivity Type_Swimming - Cliff JumpingActivity Type_Swimming - CoastalActivity Type_Swimming - FacilitiesActivity Type_Swimming - Flat WaterActivity Type_Swimming - SwiftwaterActivity Type_Townsite ActivityActivity Type_Tram/Ski Lift/GondolaActivity Type_Tubing / River DriftingActivity Type_UnknownActivity Type_Via-FerrataActivity Type_nanResponse Type_Response Type_Assist VisitorResponse Type_Assist other AgencyResponse Type_Assist other Field UnitResponse Type_Attractant ManagementResponse Type_Aversive ConditioningResponse Type_Capture and transport to captivityResponse Type_Clean UpResponse Type_Close AreaResponse Type_Close RoadResponse Type_CollarResponse Type_Collect SampleResponse Type_CullResponse Type_Destroy AnimalResponse Type_DisentangleResponse Type_Dispatch other AgencyResponse Type_Disperse Wildlife JamResponse Type_Dispose CarcassResponse Type_Ear TagResponse Type_EuthanizeResponse Type_Evacuate VisitorResponse Type_Haze - HardResponse Type_Haze - SoftResponse Type_Immobilize AnimalResponse Type_Inform VisitorResponse Type_Infrastructure modificationResponse Type_Investigate IncidentResponse Type_Issue Prohibited Activity OrderResponse Type_Issue Restricted Activity OrderResponse Type_Issue Stop Work OrderResponse Type_Leave on LandscapeResponse Type_Mark - paintResponse Type_Monitor - CameraResponse Type_Monitor - patrolResponse Type_Monitor - visitor and staff sightingResponse Type_NecropsyResponse Type_No response requiredResponse Type_Not ApplicableResponse Type_Refer incident to other agencyResponse Type_Rehabilitate areaResponse Type_Relocate animal (s)Response Type_Request assistance - other AgencyResponse Type_Request assistance - policeResponse Type_Traffic controlResponse Type_TranslocateResponse Type_Trap or snareResponse Type_Unable to respondResponse Type_Warning signsResponse Type_nan
0BAN2010-0003.3BAN2010-00032010-01-01Banff Field UnitBanff National Park of CanadaHuman Wildlife Interaction51.161093-115.593386Yes1.02.33Coyote2.0HealthyNaNAvoidanceSurprisePrey animal (natural)Presence of Officer/PersonNaN0.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.01.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.01.00.00.00.00.00.00.00.00.01.00.00.00.00.00.00.01.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.0
1BAN2010-0003.2BAN2010-00032010-01-01Banff Field UnitBanff National Park of CanadaHuman Wildlife Interaction51.161093-115.593386Yes1.02.33Elk1.0DeadPredationNaNNaNNaNNaNNaN0.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.01.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.01.00.00.00.00.00.00.00.00.01.00.00.00.00.00.00.01.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.0
2BAN2010-0003.1BAN2010-00032010-01-01Banff Field UnitBanff National Park of CanadaHuman Wildlife Interaction51.161093-115.593386Yes1.02.33Wolf3.0Not LocatedNaNNaNNaNPrey animal (natural)NaNNaN0.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.01.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.01.00.00.00.00.00.00.00.00.01.00.00.00.00.00.00.01.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.0
3JNP2010-0011.1JNP2010-00112010-01-01Jasper Field UnitJasper National Park of CanadaRescued/Recovered/Found Wildlife53.139120-117.964219Yes1.01.00White-tailed Deer1.0DeadCollisionNaNNaNNaNNaNNaN0.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.01.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.01.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.0
4JNP2010-0015.1JNP2010-00152010-01-01Jasper Field UnitJasper National Park of CanadaAttractant53.050492-118.073612Yes1.02.50None0.0NaNNaNNaNNaNGrainNaNNaN0.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.01.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.01.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.0
5JNP2010-0023.1JNP2010-00232010-01-01Jasper Field UnitJasper National Park of CanadaRescued/Recovered/Found Wildlife52.858415-118.102814Yes1.03.00Mule Deer1.0Not LocatedCollisionNaNNaNNaNNaNNaN0.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.01.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.01.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.0
6JNP2010-0016.1JNP2010-00162010-01-02Jasper Field UnitJasper National Park of CanadaRescued/Recovered/Found Wildlife52.857314-118.103110Yes1.00.50Mule Deer1.0DeadCollisionNaNNaNNaNNaNNaN0.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.01.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.01.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.0
7LL2010-000001.1LL2010-0000012010-01-02Lake Louise, Yoho and Kootenay Field UnitBanff National Park of CanadaRescued/Recovered/Found Wildlife51.303486-115.990835Yes2.02.50Moose1.0DeadCollisionNaNUnknownUnknownNaNNaN0.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.01.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.01.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.0
8PRN2010-0001.1PRN2010-00012010-01-02Coastal British Columbia Field UnitPacific Rim National Park Reserve of CanadaDomestic Animal49.081879-125.788663Yes2.03.00Domestic Dog3.0NaNNaNPhysical or Aggressive DisplayDefence of SpaceNaNNaNNaN0.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.01.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.01.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.01.0
9BAN2010-0008.1BAN2010-00082010-01-03Banff Field UnitBanff National Park of CanadaRescued/Recovered/Found Wildlife51.162756-115.549344Yes1.01.00Coyote1.0DeadUnknownNaNNaNNaNNaNNaN0.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.01.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.01.00.01.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.0
UniqueIDIncident NumberIncident DateField UnitProtected Heritage AreaIncident TypeLatitude PublicLongitude PublicWithin ParkTotal Staff InvolvedTotal Staff HoursSpecies Common NameSum of Number of AnimalsAnimal Health StatusCause of Animal Health StatusAnimal BehaviourReason for Animal BehaviourAnimal AttractantDeterrents UsedAnimal Response to DeterrentsActivity Type_Backpacking – Multiday TripsActivity Type_Beach RecreationActivity Type_Boating - Coastal/MarineActivity Type_Boating - CommercialActivity Type_Boating - Motorized Pleasure CraftActivity Type_Bush PartyActivity Type_Camping - BackcountryActivity Type_Camping - FrontcountryActivity Type_Camping - Huts and LodgesActivity Type_Camping - Winter FrontcountryActivity Type_Canoeing - FlatwaterActivity Type_Canoeing - SwiftwaterActivity Type_CanyoneeringActivity Type_Climbing - MountaineeringActivity Type_Climbing - Technical RockActivity Type_Climbing - Waterfall IceActivity Type_Commercial Transportation OperationActivity Type_CyclingActivity Type_Cycling - Mountain BikingActivity Type_Cycling - Road/Shared PathActivity Type_Cycling - WinterActivity Type_Dog WalkingActivity Type_DogsleddingActivity Type_Domestic Residence ActivityActivity Type_DrivingActivity Type_Field SportsActivity Type_FishingActivity Type_Flight - HETSActivity Type_Flight - Hang-gliding/ParapentingActivity Type_Flight - HelicopterActivity Type_Flight - Sightseeing/Site AccessActivity Type_GolfingActivity Type_Heritage Activity - Bird WatchingActivity Type_Heritage Activity - History ActivitiesActivity Type_Heritage Activity - Photography and ArtActivity Type_Heritage Activity - SightseeingActivity Type_Heritage Activity - Wildlife ObservationActivity Type_Hiking / WalkingActivity Type_Horse Riding - Day TripActivity Type_Horse Riding - MultidayActivity Type_Ice SkatingActivity Type_Kayaking - CoastalActivity Type_Kayaking - FlatwaterActivity Type_Kayaking - SwiftwaterActivity Type_MooringActivity Type_Not ApplicableActivity Type_Orienteering / GeocachingActivity Type_OtherActivity Type_Paddleboarding - CoastalActivity Type_Paddleboarding - FlatwaterActivity Type_Park OperationsActivity Type_Park Ops - Avalanche ForecastingActivity Type_Park Ops - Avalanche ControlActivity Type_Park Ops - Search and RescueActivity Type_Park Ops - TrainingActivity Type_Picnicking / BBQActivity Type_Playground ActivitiesActivity Type_Rafting - FlatwaterActivity Type_Rafting - SwiftwaterActivity Type_RailwayActivity Type_Research - Scientific/SocialActivity Type_Resource Harvesting - Hunting/Fishing/Gathering/TrappingActivity Type_Roller SportsActivity Type_Running - RoadActivity Type_Running - TrailActivity Type_Sail Sports - Wind / Kite SurfingActivity Type_ScramblingActivity Type_Skiing - CrosscountryActivity Type_Skiing/Boarding - BackcountryActivity Type_Skiing/Boarding - Ski Resort In BoundsActivity Type_Skiing/Boarding - Ski Resort Out of BoundsActivity Type_Sledding/TobogganningActivity Type_SnowmobilingActivity Type_SnowshoeingActivity Type_Special Event - Participative AudienceActivity Type_Special Events - Passive AudienceActivity Type_Stakeholder OperationsActivity Type_SurfingActivity Type_Swimming - Cliff JumpingActivity Type_Swimming - CoastalActivity Type_Swimming - FacilitiesActivity Type_Swimming - Flat WaterActivity Type_Swimming - SwiftwaterActivity Type_Townsite ActivityActivity Type_Tram/Ski Lift/GondolaActivity Type_Tubing / River DriftingActivity Type_UnknownActivity Type_Via-FerrataActivity Type_nanResponse Type_Response Type_Assist VisitorResponse Type_Assist other AgencyResponse Type_Assist other Field UnitResponse Type_Attractant ManagementResponse Type_Aversive ConditioningResponse Type_Capture and transport to captivityResponse Type_Clean UpResponse Type_Close AreaResponse Type_Close RoadResponse Type_CollarResponse Type_Collect SampleResponse Type_CullResponse Type_Destroy AnimalResponse Type_DisentangleResponse Type_Dispatch other AgencyResponse Type_Disperse Wildlife JamResponse Type_Dispose CarcassResponse Type_Ear TagResponse Type_EuthanizeResponse Type_Evacuate VisitorResponse Type_Haze - HardResponse Type_Haze - SoftResponse Type_Immobilize AnimalResponse Type_Inform VisitorResponse Type_Infrastructure modificationResponse Type_Investigate IncidentResponse Type_Issue Prohibited Activity OrderResponse Type_Issue Restricted Activity OrderResponse Type_Issue Stop Work OrderResponse Type_Leave on LandscapeResponse Type_Mark - paintResponse Type_Monitor - CameraResponse Type_Monitor - patrolResponse Type_Monitor - visitor and staff sightingResponse Type_NecropsyResponse Type_No response requiredResponse Type_Not ApplicableResponse Type_Refer incident to other agencyResponse Type_Rehabilitate areaResponse Type_Relocate animal (s)Response Type_Request assistance - other AgencyResponse Type_Request assistance - policeResponse Type_Traffic controlResponse Type_TranslocateResponse Type_Trap or snareResponse Type_Unable to respondResponse Type_Warning signsResponse Type_nan
736482021-HWC-0000-JASFU-2861.12021-HWC-0000-JASFU-28612021-12-31Jasper Field UnitJasper National Park of CanadaHuman Wildlife Interaction52.876739-118.091588Yes1.00.666667Mule Deer1.0NaNNaNPresence - Wildlife Exclusion ZonesNaNNaNNaNNaN0.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.01.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.01.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.0
736492021-HWC-0000-JASFU-2862.12021-HWC-0000-JASFU-28622021-12-31Jasper Field UnitJasper National Park of CanadaRescued/Recovered/Found Wildlife53.093617-118.030592Yes1.02.000000Bighorn Sheep1.0InjuredUnknownNaNNaNNaNNaNNaN0.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.01.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.01.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.0
736502021-HWC-0574-JASFU-0016.22021-HWC-0574-JASFU-00162021-12-31Jasper Field UnitJasper National Park of CanadaHuman Wildlife Interaction52.860896-118.087098Yes1.00.166667Elk1.0NaNNaNNaNNaNNaNNaNNaN0.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.01.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.01.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.0
736512021-HWC-0574-JASFU-0016.12021-HWC-0574-JASFU-00162021-12-31Jasper Field UnitJasper National Park of CanadaHuman Wildlife Interaction52.860896-118.087098Yes1.00.166667Elk1.0NaNNaNPresence - Wildlife Exclusion ZonesNaNNaNNaNNaN0.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.01.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.01.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.0
736522021-HWC-1114-YKLLFU-0033.12021-HWC-1114-YKLLFU-00332021-12-31Lake Louise, Yoho and Kootenay Field UnitBanff National Park of CanadaAttractant51.380551-116.147884Yes1.01.750000None0.0NaNNaNNaNNaNNaNNaNNaN0.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.01.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.01.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.0
736532022-HWC-0574-JASFU-0001.22022-HWC-0574-JASFU-00012021-12-31Jasper Field UnitJasper National Park of CanadaHuman Wildlife Interaction53.162687-117.964186Yes1.00.500000Bighorn Sheep10.0NaNNaNNaNNaNNaNNaNNaN0.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.01.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.01.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.0
736542022-HWC-0574-JASFU-0001.12022-HWC-0574-JASFU-00012021-12-31Jasper Field UnitJasper National Park of CanadaHuman Wildlife Interaction53.162687-117.964186Yes1.00.500000Bighorn Sheep1.0NaNNaNIndifferent to People/VehiclesNaNNaNNaNNaN0.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.01.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.01.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.0
736552021-VS-0748-YKLLFU-00012021-VS-0748-YKLLFU-00012021-06-19Banff Field UnitBanff National Park of CanadaHighway Fence IntrusionNaNNaNYes1.01.000000NaNNaNNaNNaNNaNNaNNaNNaNNaN0.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.01.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.0NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
73656PEINP2011-0131PEINP2011-01312011-07-08Prince Edward Island Field UnitPrince Edward Island National Park of CanadaRescued/Recovered/Found Wildlife46.496335-63.406292Yes1.00.330000NaNNaNNaNNaNNaNNaNNaNNaNNaN0.00.00.00.00.00.00.01.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.01.00.00.00.00.00.00.01.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.0
736572019-HWC-0000-BANFU-14572019-HWC-0000-BANFU-14572019-08-20Banff Field UnitBanff National Park of CanadaHuman Wildlife InteractionNaNNaNYes1.00.000000NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN